Changes for page Requirements

Last modified by Robert Schaub on 2026/02/08 21:32

From 7.2 to 7.1

From version 7.1

edited by Robert Schaub
on 2025/12/24 21:53

Change comment: Imported from XAR

To version 1.1

edited by Robert Schaub
on 2025/12/18 12:03

Change comment: Imported from XAR

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@@ -1,40 +1,10 @@
  = Requirements =
--
--{{info}}
--**Phase Assignments:** See [[Requirements Roadmap Matrix>>FactHarbor.Roadmap.Requirements-Roadmap-Matrix.WebHome]] for which requirements are implemented in which phases.
--{{/info}}
--
--**This page defines Roles, Content States, Rules, and System Requirements for FactHarbor.**
--
++This page defines **Roles**, **Content States**, **Rules**, and **System Principles** for FactHarbor.
  **Core Philosophy:** Invest in system improvement, not manual data correction. When AI makes errors, improve the algorithm and re-process automatically.
--
--== Navigation ==
--
--* **[[User Needs>>FactHarbor.Specification.Requirements.User Needs.WebHome]]** - What users need from FactHarbor (drives these requirements)
--* **This page** - How we fulfill those needs through system design
--
--(% class="box infomessage" %)
--(((
--**How to read this page:**
--
--1. **User Needs drive Requirements**: See [[User Needs>>FactHarbor.Specification.Requirements.User Needs.WebHome]] for what users need
--2. **Requirements define implementation**: This page shows how we fulfill those needs
--3. **Functional Requirements (FR)**: Specific features and capabilities
--4. **Non-Functional Requirements (NFR)**: Quality attributes (performance, security, etc.)
--
--Each requirement references which User Needs it fulfills.
--)))
--
  == 1. Roles ==
--
--**Fulfills**: UN-12 (Submit claims), UN-13 (Cite verdicts), UN-14 (API access)
--
  FactHarbor uses three simple roles plus a reputation system.
--
  === 1.1 Reader ===
--
  **Who**: Anyone (no login required)
--
  **Can**:
  * Browse and search claims
  * View scenarios, evidence, verdicts, and confidence scores
@@ -41,17 +41,11 @@
  * Flag issues or errors
  * Use filters, search, and visualization tools
  * Submit claims automatically (new claims added if not duplicates)
--
  **Cannot**:
  * Modify content
  * Access edit history details
--
--**User Needs served**: UN-1 (Trust assessment), UN-2 (Claim verification), UN-3 (Article summary with FactHarbor analysis summary), UN-4 (Social media fact-checking), UN-5 (Source tracing), UN-7 (Evidence transparency), UN-8 (Understanding disagreement), UN-12 (Submit claims), UN-17 (In-article highlighting)
--
  === 1.2 Contributor ===
--
  **Who**: Registered users (earns reputation through contributions)
--
  **Can**:
  * Everything a Reader can do
  * Edit claims, evidence, and scenarios
@@ -59,7 +59,6 @@
  * Suggest improvements to AI-generated content
  * Participate in discussions
  * Earn reputation points for quality contributions
--
  **Reputation System**:
  * New contributors: Limited edit privileges
  * Established contributors (established reputation): Full edit access
@@ -66,17 +66,11 @@
  * Trusted contributors (substantial reputation): Can approve certain changes
  * Reputation earned through: Accepted edits, helpful flags, quality contributions
  * Reputation lost through: Reverted edits, invalid flags, abuse
--
  **Cannot**:
  * Delete or hide content (only moderators)
  * Override moderation decisions
--
--**User Needs served**: UN-13 (Cite and contribute)
--
  === 1.3 Moderator ===
--
  **Who**: Trusted community members with proven track record, appointed by governance board
--
  **Can**:
  * Review flagged content
  * Hide harmful or abusive content
@@ -84,26 +84,19 @@
  * Issue warnings or temporary bans
  * Make final decisions on content disputes
  * Access full audit logs
--
  **Cannot**:
  * Change governance rules
  * Permanently ban users without board approval
  * Override technical quality gates
--
  **Note**: Small team (3-5 initially), supported by automated moderation tools.
--
  === 1.4 Domain Trusted Contributors (Optional, Task-Specific) ===
--
  **Who**: Subject matter specialists invited for specific high-stakes disputes
--
  **Not a permanent role**: Contacted externally when needed for contested claims in their domain
--
  **When used**:
  * Medical claims with life/safety implications
  * Legal interpretations with significant impact
  * Scientific claims with high controversy
  * Technical claims requiring specialized knowledge
--
  **Process**:
  * Moderator identifies need for expert input
  * Contact expert externally (don't require them to be users)
@@ -110,24 +110,14 @@
  * Trusted Contributor provides written opinion with sources
  * Opinion added to claim record
  * Trusted Contributor acknowledged in claim
--
--**User Needs served**: UN-16 (Expert validation status)
--
  == 2. Content States ==
--
--**Fulfills**: UN-1 (Trust indicators), UN-16 (Review status transparency)
--
  FactHarbor uses two content states. Focus is on transparency and confidence scoring, not gatekeeping.
--
  === 2.1 Published ===
--
  **Status**: Visible to all users
--
  **Includes**:
  * AI-generated analyses (default state)
  * User-contributed content
  * Edited/improved content
--
  **Quality Indicators** (displayed with content):
  * **Confidence Score**: 0-100% (AI's confidence in analysis)
  * **Source Quality Score**: 0-100% (based on source track record)
@@ -135,20 +135,13 @@
  * **Completeness Score**: % of expected fields filled
  * **Last Updated**: Date of most recent change
  * **Edit Count**: Number of revisions
--* **Review Status**: AI-generated / Human-reviewed / Expert-validated
--
  **Automatic Warnings**:
  * Confidence < 60%: "Low confidence - use caution"
  * Source quality < 40%: "Sources may be unreliable"
  * High controversy: "Disputed - multiple interpretations exist"
  * Medical/Legal/Safety domain: "Seek professional advice"
--
--**User Needs served**: UN-1 (Trust score), UN-9 (Methodology transparency), ~~UN-15 (Evolution timeline - Deferred)~~, UN-16 (Review status)
--
  === 2.2 Hidden ===
--
  **Status**: Not visible to regular users (only to moderators)
--
  **Reasons**:
  * Spam or advertising
  * Personal attacks or harassment
@@ -156,29 +156,21 @@
  * Privacy violations
  * Deliberate misinformation (verified)
  * Abuse or harmful content
--
  **Process**:
  * Automated detection flags for moderator review
  * Moderator confirms and hides
  * Original author notified with reason
  * Can appeal to board if disputes moderator decision
--
  **Note**: Content is hidden, not deleted (for audit trail)
--
  == 3. Contribution Rules ==
--
  === 3.1 All Contributors Must ===
--
  * Provide sources for factual claims
  * Use clear, neutral language in FactHarbor's own summaries
  * Respect others and maintain civil discourse
  * Accept community feedback constructively
  * Focus on improving quality, not protecting ego
--
  === 3.2 AKEL (AI System) ===
--
  **AKEL is the primary system**. Human contributions supplement and train AKEL.
--
  **AKEL Must**:
  * Mark all outputs as AI-generated
  * Display confidence scores prominently
@@ -186,74 +186,49 @@
  * Flag uncertainty clearly
  * Identify contradictions in evidence
  * Learn from human corrections
--
  **When AKEL Makes Errors**:
 . Capture the error pattern (what, why, how common)
 . Improve the system (better prompt, model, validation)
 . Re-process affected claims automatically
 . Measure improvement (did quality increase?)
--
  **Human Role**: Train AKEL through corrections, not replace AKEL
--
  === 3.3 Contributors Should ===
--
  * Improve clarity and structure
  * Add missing sources
  * Flag errors for system improvement
  * Suggest better ways to present information
  * Participate in quality discussions
--
  === 3.4 Moderators Must ===
--
  * Be impartial
  * Document moderation decisions
  * Respond to appeals promptly
  * Use automated tools to scale efforts
  * Focus on abuse/harm, not routine quality control
--
  == 4. Quality Standards ==
--
--**Fulfills**: UN-5 (Source reliability), UN-6 (Publisher track records), UN-7 (Evidence transparency), UN-9 (Methodology transparency)
--
  === 4.1 Source Requirements ===
--
  **Track Record Over Credentials**:
  * Sources evaluated by historical accuracy
  * Correction policy matters
  * Independence from conflicts of interest
  * Methodology transparency
--
  **Source Quality Database**:
  * Automated tracking of source accuracy
  * Correction frequency
  * Reliability score (updated continuously)
  * Users can see source track record
--
  **No automatic trust** for government, academia, or media - all evaluated by track record.
--
--**User Needs served**: UN-5 (Source provenance), UN-6 (Publisher reliability)
--
  === 4.2 Claim Requirements ===
--
  * Clear subject and assertion
  * Verifiable with available information
  * Sourced (or explicitly marked as needing sources)
  * Neutral language in FactHarbor summaries
  * Appropriate context provided
--
--**User Needs served**: UN-2 (Claim extraction and verification)
--
  === 4.3 Evidence Requirements ===
--
  * Publicly accessible (or explain why not)
  * Properly cited with attribution
  * Relevant to claim being evaluated
  * Original source preferred over secondary
--
--**User Needs served**: UN-7 (Evidence transparency)
--
  === 4.4 Confidence Scoring ===
--
  **Automated confidence calculation based on**:
  * Source quality scores
  * Evidence consistency
@@ -260,23 +260,14 @@
  * Contradiction detection
  * Completeness of analysis
  * Historical accuracy of similar claims
--
  **Thresholds**:
  * < 40%: Too low to publish (needs improvement)
  * 40-60%: Published with "Low confidence" warning
  * 60-80%: Published as standard
  * 80-100%: Published as "High confidence"
--
--**User Needs served**: UN-1 (Trust assessment), UN-9 (Methodology transparency)
--
  == 5. Automated Risk Scoring ==
--
--**Fulfills**: UN-10 (Manipulation detection), UN-16 (Appropriate review level)
--
  **Replace manual risk tiers with continuous automated scoring**.
--
  === 5.1 Risk Score Calculation ===
--
  **Factors** (weighted algorithm):
  * **Domain sensitivity**: Medical, legal, safety auto-flagged higher
  * **Potential impact**: Views, citations, spread
@@ -283,26 +283,16 @@
  * **Controversy level**: Flags, disputes, edit wars
  * **Uncertainty**: Low confidence, contradictory evidence
  * **Source reliability**: Track record of sources used
--
  **Score**: 0-100 (higher = more risk)
--
  === 5.2 Automated Actions ===
--
  * **Score > 80**: Flag for moderator review before publication
  * **Score 60-80**: Publish with prominent warnings
  * **Score 40-60**: Publish with standard warnings
  * **Score < 40**: Publish normally
--
  **Continuous monitoring**: Risk score recalculated as new information emerges
--
--**User Needs served**: UN-10 (Detect manipulation tactics), UN-16 (Review status)
--
  == 6. System Improvement Process ==
--
  **Core principle**: Fix the system, not just the data.
--
  === 6.1 Error Capture ===
--
  **When users flag errors or make corrections**:
 . What was wrong? (categorize)
 . What should it have been?
@@ -309,9 +309,7 @@
 . Why did the system fail? (root cause)
 . How common is this pattern?
 . Store in ErrorPattern table (improvement queue)
--
--=== 6.2 Continuous Improvement Cycle ===
--
++=== 6.2 Weekly Improvement Cycle ===
 . **Review**: Analyze top error patterns
 . **Develop**: Create fix (prompt, model, validation)
 . **Test**: Validate fix on sample claims
@@ -318,9 +318,7 @@
 . **Deploy**: Roll out if quality improves
 . **Re-process**: Automatically update affected claims
 . **Monitor**: Track quality metrics
--
  === 6.3 Quality Metrics Dashboard ===
--
  **Track continuously**:
  * Error rate by category
  * Source quality distribution
@@ -329,23 +329,16 @@
  * Correction acceptance rate
  * Re-work rate
  * Claims processed per hour
--
--**Goal**: continuous improvement in error rate
--
++**Goal**: 10% monthly improvement in error rate
  == 7. Automated Quality Monitoring ==
--
  **Replace manual audit sampling with automated monitoring**.
--
  === 7.1 Continuous Metrics ===
--
  * **Source quality**: Track record database
  * **Consistency**: Contradiction detection
  * **Clarity**: Readability scores
  * **Completeness**: Field validation
  * **Accuracy**: User corrections tracked
--
  === 7.2 Anomaly Detection ===
--
  **Automated alerts for**:
  * Sudden quality drops
  * Unusual patterns
@@ -352,1622 +352,142 @@
  * Contradiction clusters
  * Source reliability changes
  * User behavior anomalies
--
  === 7.3 Targeted Review ===
--
  * Review only flagged items
  * Random sampling for calibration (not quotas)
  * Learn from corrections to improve automation
--
--== 8. Functional Requirements ==
--
--This section defines specific features that fulfill user needs.
--
--=== 8.1 Claim Intake & Normalization ===
--
--==== FR1 — Claim Intake ====
--
--**Fulfills**: UN-2 (Claim extraction), UN-4 (Quick fact-checking), UN-12 (Submit claims)
--
++== 8. Claim Intake & Normalization ==
++=== 8.1 FR1 – Claim Intake ===
  * Users submit claims via simple form or API
  * Claims can be text, URL, or image
  * Duplicate detection (semantic similarity)
  * Auto-categorization by domain
--
--==== FR2 — Claim Normalization ====
--
--**Fulfills**: UN-2 (Claim verification)
--
++=== 8.2 FR2 – Claim Normalization ===
  * Standardize to clear assertion format
  * Extract key entities (who, what, when, where)
  * Identify claim type (factual, predictive, evaluative)
  * Link to existing similar claims
--
--==== FR3 — Claim Classification ====
--
--**Fulfills**: UN-11 (Filtered research)
--
++=== 8.3 FR3 – Claim Classification ===
  * Domain: Politics, Science, Health, etc.
  * Type: Historical fact, current stat, prediction, etc.
  * Risk score: Automated calculation
  * Complexity: Simple, moderate, complex
--
--=== 8.2 Scenario System ===
--
--==== FR4 — Scenario Generation ====
--
--**Fulfills**: UN-2 (Context-dependent verification), UN-3 (Article summary with FactHarbor analysis summary), UN-8 (Understanding disagreement)
--
++== 9. Scenario System ==
++=== 9.1 FR4 – Scenario Generation ===
  **Automated scenario creation**:
--* AKEL analyzes claim and generates likely scenarios (use-cases and contexts)
--* Each scenario includes: assumptions, definitions, boundaries, evidence context
++* AKEL analyzes claim and generates likely scenarios
++* Each scenario includes: assumptions, evidence, conclusion
  * Users can flag incorrect scenarios
  * System learns from corrections
--
--**Key Concept**: Scenarios represent different interpretations or contexts (e.g., "Clinical trials with healthy adults" vs. "Real-world data with diverse populations")
--
--==== FR5 — Evidence Linking ====
--
--**Fulfills**: UN-5 (Source tracing), UN-7 (Evidence transparency)
--
++=== 9.2 FR5 – Evidence Linking ===
  * Automated evidence discovery from sources
  * Relevance scoring
  * Contradiction detection
  * Source quality assessment
--
--==== FR6 — Scenario Comparison ====
--
--**Fulfills**: UN-3 (Article summary with FactHarbor analysis summary), UN-8 (Understanding disagreement)
--
++=== 9.3 FR6 – Scenario Comparison ===
  * Side-by-side comparison interface
--* Highlight key differences between scenarios
--* Show evidence supporting each scenario
--* Display confidence scores per scenario
--
--=== 8.3 Verdicts & Analysis ===
--
--==== FR7 — Automated Verdicts ====
--
--**Fulfills**: UN-1 (Trust score), UN-2 (Verification verdicts), UN-3 (Article summary with FactHarbor analysis summary), UN-13 (Cite verdicts)
--
--* AKEL generates verdict based on evidence within each scenario
--* **Likelihood range** displayed (e.g., "0.70-0.85 (likely true)") - NOT binary true/false
--* **Uncertainty factors** explicitly listed (e.g., "Small sample sizes", "Long-term effects unknown")
++* Highlight key differences
++* Show evidence supporting each
++* Display confidence scores
++== 10. Verdicts & Analysis ==
++=== 10.1 FR7 – Automated Verdicts ===
++* AKEL generates verdict based on evidence
  * Confidence score displayed prominently
--* Source quality indicators shown
++* Source quality indicators
  * Contradictions noted
  * Uncertainty acknowledged
--
--**Key Innovation**: Detailed probabilistic verdicts with explicit uncertainty, not binary judgments
--
--==== FR8 — Time Evolution ====
--
--{{warning}}
--**Status:** Deferred (Not in V1.0)
--
--This requirement has been **dropped from the current architecture and design**. Versioned entities have been replaced with simple edit history tracking only. Full evolution timeline functionality is deferred to future releases beyond V1.0.
--{{/warning}}
--
--**Fulfills**: UN-15 (Verdict evolution timeline)
--
--* Claims and verdicts update as new evidence emerges
--* Version history maintained for all verdicts
++=== 10.2 FR8 – Time Evolution ===
++* Claims update as new evidence emerges
++* Version history maintained
  * Changes highlighted
  * Confidence score trends visible
--* Users can see "as of date X, what did we know?"
--
--=== 8.4 User Interface & Presentation ===
--
--==== FR12 — Two-Panel Summary View (Article Summary with FactHarbor Analysis Summary) ====
--
--**Fulfills**: UN-3 (Article Summary with FactHarbor Analysis Summary)
--
--**Purpose**: Provide side-by-side comparison of what a document claims vs. FactHarbor's complete analysis of its credibility
--
--**Left Panel: Article Summary**:
--* Document title, source, and claimed credibility
--* "The Big Picture" - main thesis or position change
--* "Key Findings" - structured summary of document's main claims
--* "Reasoning" - document's explanation for positions
--* "Conclusion" - document's bottom line
--
--**Right Panel: FactHarbor Analysis Summary**:
--* FactHarbor's independent source credibility assessment
--* Claim-by-claim verdicts with confidence scores
--* Methodology assessment (strengths, limitations)
--* Overall verdict on document quality
--* Analysis ID for reference
--
--**Design Principles**:
--* No scrolling required - both panels visible simultaneously
--* Visual distinction between "what they say" and "FactHarbor's analysis"
--* Color coding for verdicts (supported, uncertain, refuted)
--* Confidence percentages clearly visible
--* Mobile responsive (panels stack vertically on small screens)
--
--**Implementation Notes**:
--* Generated automatically by AKEL for every analyzed document
--* Updates when verdict evolves (maintains version history)
--* Exportable as standalone summary report
--* Shareable via permanent URL
--
--==== FR13 — In-Article Claim Highlighting ====
--
--**Fulfills**: UN-17 (In-article claim highlighting)
--
--**Purpose**: Enable readers to quickly assess claim credibility while reading by visually highlighting factual claims with color-coded indicators
--
--==== Visual Example: Article with Highlighted Claims ====
--
--(% class="box" %)
--(((
--**Article: "New Study Shows Benefits of Mediterranean Diet"**
--
--A recent study published in the Journal of Nutrition has revealed new findings about the Mediterranean diet.
--
--(% class="box successmessage" style="margin:10px 0;" %)
--(((
--🟢 **Researchers found that Mediterranean diet followers had a 25% lower risk of heart disease compared to control groups**
--
--(% style="font-size:0.9em; color:#666;" %)
--↑ WELL SUPPORTED • 87% confidence
--[[Click for evidence details →]]
--(%%)
--)))
--
--The study, which followed 10,000 participants over five years, showed significant improvements in cardiovascular health markers.
--
--(% class="box warningmessage" style="margin:10px 0;" %)
--(((
--🟡 **Some experts believe this diet can completely prevent heart attacks**
--
--(% style="font-size:0.9em; color:#666;" %)
--↑ UNCERTAIN • 45% confidence
--Overstated - evidence shows risk reduction, not prevention
--[[Click for details →]]
--(%%)
--)))
--
--Dr. Maria Rodriguez, lead researcher, recommends incorporating more olive oil, fish, and vegetables into daily meals.
--
--(% class="box errormessage" style="margin:10px 0;" %)
--(((
--🔴 **The study proves that saturated fats cause heart disease**
--
--(% style="font-size:0.9em; color:#666;" %)
--↑ REFUTED • 15% confidence
--Claim not supported by study design; correlation ≠ causation
--[[Click for counter-evidence →]]
--(%%)
--)))
--
--Participants also reported feeling more energetic and experiencing better sleep quality, though these were secondary measures.
--)))
--
--**Legend:**
--* 🟢 = Well-supported claim (confidence ≥75%)
--* 🟡 = Uncertain claim (confidence 40-74%)
--* 🔴 = Refuted/unsupported claim (confidence <40%)
--* Plain text = Non-factual content (context, opinions, recommendations)
--
--==== Tooltip on Hover/Click ====
--
--(% class="box infomessage" %)
--(((
--**FactHarbor Analysis**
--
--**Claim:**
--"Researchers found that Mediterranean diet followers had a 25% lower risk of heart disease"
--
--**Verdict:** WELL SUPPORTED
--**Confidence:** 87%
--
--**Evidence Summary:**
--* Meta-analysis of 12 RCTs confirms 23-28% risk reduction
--* Consistent findings across multiple populations
--* Published in peer-reviewed journal (high credibility)
--
--**Uncertainty Factors:**
--* Exact percentage varies by study (20-30% range)
--
--[[View Full Analysis →]]
--)))
--
--**Color-Coding System**:
--* **Green**: Well-supported claims (confidence ≥75%, strong evidence)
--* **Yellow/Orange**: Uncertain claims (confidence 40-74%, conflicting or limited evidence)
--* **Red**: Refuted or unsupported claims (confidence <40%, contradicted by evidence)
--* **Gray/Neutral**: Non-factual content (opinions, questions, procedural text)
--
--==== Interactive Highlighting Example (Detailed View) ====
--
--(% style="width:100%; border-collapse:collapse;" %)
--|=**Article Text**|=**Status**|=**Analysis**
--|(((A recent study published in the Journal of Nutrition has revealed new findings about the Mediterranean diet.)))|(% style="text-align:center;" %)Plain text|(% style="font-style:italic; color:#888;" %)Context - no highlighting
--|(((//Researchers found that Mediterranean diet followers had a 25% lower risk of heart disease compared to control groups//)))|(% style="background-color:#D4EDDA; text-align:center; padding:8px;" %)🟢 **WELL SUPPORTED**|(((
--**87% confidence**
--
--Meta-analysis of 12 RCTs confirms 23-28% risk reduction
--
--[[View Full Analysis]]
--)))
--|(((The study, which followed 10,000 participants over five years, showed significant improvements in cardiovascular health markers.)))|(% style="text-align:center;" %)Plain text|(% style="font-style:italic; color:#888;" %)Methodology - no highlighting
--|(((//Some experts believe this diet can completely prevent heart attacks//)))|(% style="background-color:#FFF3CD; text-align:center; padding:8px;" %)🟡 **UNCERTAIN**|(((
--**45% confidence**
--
--Overstated - evidence shows risk reduction, not prevention
--
--[[View Details]]
--)))
--|(((Dr. Rodriguez recommends incorporating more olive oil, fish, and vegetables into daily meals.)))|(% style="text-align:center;" %)Plain text|(% style="font-style:italic; color:#888;" %)Recommendation - no highlighting
--|(((//The study proves that saturated fats cause heart disease//)))|(% style="background-color:#F8D7DA; text-align:center; padding:8px;" %)🔴 **REFUTED**|(((
--**15% confidence**
--
--Claim not supported by study; correlation ≠ causation
--
--[[View Counter-Evidence]]
--)))
--
--**Design Notes:**
--* Highlighted claims use italics to distinguish from plain text
--* Color backgrounds match XWiki message box colors (success/warning/error)
--* Status column shows verdict prominently
--* Analysis column provides quick summary with link to details
--
--**User Actions**:
--* **Hover** over highlighted claim → Tooltip appears
--* **Click** highlighted claim → Detailed analysis modal/panel
--* **Toggle** button to turn highlighting on/off
--* **Keyboard**: Tab through highlighted claims
--
--**Interaction Design**:
--* Hover/click on highlighted claim → Show tooltip with:
-- * Claim text
-- * Verdict (e.g., "WELL SUPPORTED")
-- * Confidence score (e.g., "85%")
-- * Brief evidence summary
-- * Link to detailed analysis
--* Toggle highlighting on/off (user preference)
--* Adjustable color intensity for accessibility
--
--**Technical Requirements**:
--* Real-time highlighting as page loads (non-blocking)
--* Claim boundary detection (start/end of assertion)
--* Handle nested or overlapping claims
--* Preserve original article formatting
--* Work with various content formats (HTML, plain text, PDFs)
--
--**Performance Requirements**:
--* Highlighting renders within 500ms of page load
--* No perceptible delay in reading experience
--* Efficient DOM manipulation (avoid reflows)
--
--**Accessibility**:
--* Color-blind friendly palette (use patterns/icons in addition to color)
--* Screen reader compatible (ARIA labels for claim credibility)
--* Keyboard navigation to highlighted claims
--
--**Implementation Notes**:
--* Claims extracted and analyzed by AKEL during initial processing
--* Highlighting data stored as annotations with byte offsets
--* Client-side rendering of highlights based on verdict data
--* Mobile responsive (tap instead of hover)
--
--=== 8.5 Workflow & Moderation ===
--
--==== FR9 — Publication Workflow ====
--
--**Fulfills**: UN-1 (Fast access to verified content), UN-16 (Clear review status)
--
++== 11. Workflow & Moderation ==
++=== 11.1 FR9 – Publication Workflow ===
  **Simple flow**:
 . Claim submitted
 . AKEL processes (automated)
--3. If confidence > threshold: Publish (labeled as AI-generated)
++3. If confidence > threshold: Publish
 . If confidence < threshold: Flag for improvement
 . If risk score > threshold: Flag for moderator
--
  **No multi-stage approval process**
--
--==== FR10 — Moderation ====
--
++=== 11.2 FR10 – Moderation ===
  **Focus on abuse, not routine quality**:
  * Automated abuse detection
  * Moderators handle flags
  * Quick response to harmful content
  * Minimal involvement in routine content
--
--==== FR11 — Audit Trail ====
--
--**Fulfills**: UN-14 (API access to histories), UN-15 (Evolution tracking)
--
++=== 11.3 FR11 – Audit Trail ===
  * All edits logged
  * Version history public
  * Moderation decisions documented
  * System improvements tracked
--
--== 9. Non-Functional Requirements ==
--
--=== 9.1 NFR1 — Performance ===
--
--**Fulfills**: UN-4 (Fast fact-checking), UN-11 (Responsive filtering)
--
++== 12. Technical Requirements ==
++=== 12.1 NFR1 – Performance ===
  * Claim processing: < 30 seconds
  * Search response: < 2 seconds
  * Page load: < 3 seconds
  * 99% uptime
--
--=== 9.2 NFR2 — Scalability ===
--
--**Fulfills**: UN-14 (API access at scale)
--
++=== 12.2 NFR2 – Scalability ===
  * Handle 10,000 claims initially
  * Scale to 1M+ claims
  * Support 100K+ concurrent users
  * Automated processing scales linearly
--
--=== 9.3 NFR3 — Transparency ===
--
--**Fulfills**: UN-7 (Evidence transparency), UN-9 (Methodology transparency), UN-13 (Citable verdicts), UN-15 (Evolution visibility)
--
++=== 12.3 NFR3 – Transparency ===
  * All algorithms open source
  * All data exportable
  * All decisions documented
  * Quality metrics public
--
--=== 9.4 NFR4 — Security & Privacy ===
--
++=== 12.4 NFR4 – Security & Privacy ===
  * Follow [[Privacy Policy>>FactHarbor.Organisation.How-We-Work-Together.Privacy-Policy]]
  * Secure authentication
  * Data encryption
  * Regular security audits
--
--=== 9.5 NFR5 — Maintainability ===
--
++=== 12.5 NFR5 – Maintainability ===
  * Modular architecture
  * Automated testing
  * Continuous integration
  * Comprehensive documentation
--
--=== NFR11: AKEL Quality Assurance Framework ===
--
--**Fulfills:** AI safety, IFCN methodology transparency
--
--**Specification:**
--
--Multi-layer AI quality gates to detect hallucinations, low-confidence results, and logical inconsistencies.
--
--==== Quality Gate 1: Claim Extraction Validation ====
--
--**Purpose:** Ensure extracted claims are factual assertions (not opinions/predictions)
--
--**Checks:**
--1. **Factual Statement Test:** Is this verifiable? (Yes/No)
--2. **Opinion Detection:** Contains hedging language? ("I think", "probably", "best")
--3. **Future Prediction Test:** Makes claims about future events?
--4. **Specificity Score:** Contains specific entities, numbers, dates?
--
--**Thresholds:**
--* Factual: Must be "Yes"
--* Opinion markers: <2 hedging phrases
--* Specificity: ≥3 specific elements
--
--**Action if Failed:** Flag as "Non-verifiable", do NOT generate verdict
--
--==== Quality Gate 2: Evidence Relevance Validation ====
--
--**Purpose:** Ensure AI-linked evidence actually relates to claim
--
--**Checks:**
--1. **Semantic Similarity Score:** Evidence vs. claim (embeddings)
--2. **Entity Overlap:** Shared people/places/things?
--3. **Topic Relevance:** Discusses claim subject?
--
--**Thresholds:**
--* Similarity: ≥0.6 (cosine similarity)
--* Entity overlap: ≥1 shared entity
--* Topic relevance: ≥0.5
--
--**Action if Failed:** Discard irrelevant evidence
--
--==== Quality Gate 3: Scenario Coherence Check ====
--
--**Purpose:** Validate scenario assumptions are logical and complete
--
--**Checks:**
--1. **Completeness:** All required fields populated
--2. **Internal Consistency:** Assumptions don't contradict
--3. **Distinguishability:** Scenarios meaningfully different
--
--**Thresholds:**
--* Required fields: 100%
--* Contradiction score: <0.3
--* Scenario similarity: <0.8
--
--**Action if Failed:** Merge duplicates, reduce confidence -20%
--
--==== Quality Gate 4: Verdict Confidence Assessment ====
--
--**Purpose:** Only publish high-confidence verdicts
--
--**Checks:**
--1. **Evidence Count:** Minimum 2 sources
--2. **Source Quality:** Average reliability ≥0.6
--3. **Evidence Agreement:** Supporting vs. contradicting ≥0.6
--4. **Uncertainty Factors:** Hedging in reasoning
--
--**Confidence Tiers:**
--* **HIGH (80-100%):** ≥3 sources, ≥0.7 quality, ≥80% agreement
--* **MEDIUM (50-79%):** ≥2 sources, ≥0.6 quality, ≥60% agreement
--* **LOW (0-49%):** <2 sources OR low quality/agreement
--* **INSUFFICIENT:** <2 sources → DO NOT PUBLISH
--
--**Implementation Phases:**
--* **POC1:** Gates 1 & 4 only (basic validation)
--* **POC2:** All 4 gates (complete framework)
--* **V1.0:** Hardened with <5% hallucination rate
--
--**Acceptance Criteria:**
--* ✅ All gates operational
--* ✅ Hallucination rate <5%
--* ✅ Quality metrics public
--
--=== NFR12: Security Controls ===
--
--**Fulfills:** Data protection, system integrity, user privacy, production readiness
--
--**Purpose:** Protect FactHarbor systems, user data, and operations from security threats, ensuring production-grade security posture.
--
--**Specification:**
--
--==== API Security ====
--
--**Rate Limiting:**
--* **Analysis endpoints:** 100 requests/hour per IP
--* **Read endpoints:** 1,000 requests/hour per IP
--* **Search:** 500 requests/hour per IP
--* **Authenticated users:** 5x higher limits
--* **Burst protection:** Max 10 requests/second
--
--**Authentication & Authorization:**
--* **API Keys:** Required for programmatic access
--* **JWT tokens:** For user sessions (1-hour expiry)
--* **OAuth2:** For third-party integrations
--* **Role-Based Access Control (RBAC):**
-- * Public: Read-only access to published claims
-- * Contributor: Submit claims, provide evidence
-- * Moderator: Review contributions, manage quality
-- * Admin: System configuration, user management
--
--**CORS Policies:**
--* Whitelist approved domains only
--* No wildcard origins in production
--* Credentials required for sensitive endpoints
--
--**Input Sanitization:**
--* Validate all user input against schemas
--* Sanitize HTML/JavaScript in text submissions
--* Prevent SQL injection (use parameterized queries)
--* Prevent command injection (no shell execution of user input)
--* Max request size: 10MB
--* File upload restrictions: Whitelist file types, scan for malware
--
-----
--
--==== Data Security ====
--
--**Encryption at Rest:**
--* Database encryption using AES-256
--* Encrypted backups
--* Key management via cloud provider KMS (AWS KMS, Google Cloud KMS)
--* Regular key rotation (90-day cycle)
--
--**Encryption in Transit:**
--* HTTPS/TLS 1.3 only (no TLS 1.0/1.1)
--* Strong cipher suites only
--* HSTS (HTTP Strict Transport Security) enabled
--* Certificate pinning for mobile apps
--
--**Secure Credential Storage:**
--* Passwords hashed with bcrypt (cost factor 12+)
--* API keys encrypted in database
--* Secrets stored in environment variables (never in code)
--* Use secrets manager (AWS Secrets Manager, HashiCorp Vault)
--
--**Data Privacy:**
--* Minimal data collection (privacy by design)
--* User data deletion on request (GDPR compliance)
--* PII encryption in database
--* Anonymize logs (no PII in log files)
--
-----
--
--==== Application Security ====
--
--**OWASP Top 10 Compliance:**
--
--1. **Broken Access Control:** RBAC implementation, path traversal prevention
--2. **Cryptographic Failures:** Strong encryption, secure key management
--3. **Injection:** Parameterized queries, input validation
--4. **Insecure Design:** Security review of all features
--5. **Security Misconfiguration:** Hardened defaults, security headers
--6. **Vulnerable Components:** Dependency scanning (see below)
--7. **Authentication Failures:** Strong password policy, MFA support
--8. **Data Integrity Failures:** Signature verification, checksums
--9. **Security Logging Failures:** Comprehensive audit logs
--10. **Server-Side Request Forgery:** URL validation, whitelist domains
--
--**Security Headers:**
--* `Content-Security-Policy`: Strict CSP to prevent XSS
--* `X-Frame-Options`: DENY (prevent clickjacking)
--* `X-Content-Type-Options`: nosniff
--* `Referrer-Policy`: strict-origin-when-cross-origin
--* `Permissions-Policy`: Restrict browser features
--
--**Dependency Vulnerability Scanning:**
--* **Tools:** Snyk, Dependabot, npm audit, pip-audit
--* **Frequency:** Daily automated scans
--* **Action:** Patch critical vulnerabilities within 24 hours
--* **Policy:** No known high/critical CVEs in production
--
--**Security Audits:**
--* **Internal:** Quarterly security reviews
--* **External:** Annual penetration testing by certified firm
--* **Bug Bounty:** Public bug bounty program (V1.1+)
--* **Compliance:** SOC 2 Type II certification target (V1.5)
--
-----
--
--==== Operational Security ====
--
--**DDoS Protection:**
--* CloudFlare or AWS Shield
--* Rate limiting at CDN layer
--* Automatic IP blocking for abuse patterns
--
--**Monitoring & Alerting:**
--* Real-time security event monitoring
--* Alerts for:
-- * Failed login attempts (>5 in 10 minutes)
-- * API abuse patterns
-- * Unusual data access patterns
-- * Security scan detections
--* Integration with SIEM (Security Information and Event Management)
--
--**Incident Response:**
--* Documented incident response plan
--* Security incident classification (P1-P4)
--* On-call rotation for security issues
--* Post-mortem for all security incidents
--* Public disclosure policy (coordinated disclosure)
--
--**Backup & Recovery:**
--* Daily encrypted backups
--* 30-day retention period
--* Tested recovery procedures (quarterly)
--* Disaster recovery plan (RTO: 4 hours, RPO: 1 hour)
--
-----
--
--==== Compliance & Standards ====
--
--**GDPR Compliance:**
--* User consent management
--* Right to access data
--* Right to deletion
--* Data portability
--* Privacy policy published
--
--**Accessibility:**
--* WCAG 2.1 AA compliance
--* Screen reader compatibility
--* Keyboard navigation
--* Alt text for images
--
--**Browser Support:**
--* Modern browsers only (Chrome/Edge/Firefox/Safari latest 2 versions)
--* No IE11 support
--
--**Acceptance Criteria:**
--
--* ✅ Passes OWASP ZAP security scan (no high/critical findings)
--* ✅ All dependencies with known vulnerabilities patched
--* ✅ Penetration test completed with no critical findings
--* ✅ Rate limiting blocks abuse attempts
--* ✅ Encryption at rest and in transit verified
--* ✅ Security headers scored A+ on securityheaders.com
--* ✅ Incident response plan documented and tested
--* ✅ 95% uptime over 30-day period
--
--=== NFR13: Quality Metrics Transparency ===
--
--**Fulfills:** User trust, transparency, continuous improvement, IFCN methodology transparency
--
--**Purpose:** Provide transparent, measurable quality metrics that demonstrate AKEL's performance and build user trust in automated fact-checking.
--
--**Specification:**
--
--==== Component: Public Quality Dashboard ====
--
--**Core Metrics to Display:**
--
--**1. Verdict Quality Metrics**
--
--**TIGERScore (Fact-Checking Quality):**
--* **Definition:** Measures how well generated verdicts match expert fact-checker judgments
--* **Scale:** 0-100 (higher is better)
--* **Calculation:** Using TIGERScore framework (Truth-conditional accuracy, Informativeness, Generality, Evaluativeness, Relevance)
--* **Target:** Average ≥80 for production release
--* **Display:**
--{{code}}
--Verdict Quality (TIGERScore):
--Overall: 84.2 ▲ (+2.1 from last month)
--
--Distribution:
-- Excellent (>80): 67%
-- Good (60-80): 28%
-- Needs Improvement (<60): 5%
--
--Trend: [Graph showing improvement over time]
--{{/code}}
--
--**2. Hallucination & Faithfulness Metrics**
--
--**AlignScore (Faithfulness to Evidence):**
--* **Definition:** Measures how well verdicts align with actual evidence content
--* **Scale:** 0-1 (higher is better)
--* **Purpose:** Detect AI hallucinations (making claims not supported by evidence)
--* **Target:** Average ≥0.85, hallucination rate <5%
--* **Display:**
--{{code}}
--Evidence Faithfulness (AlignScore):
--Average: 0.87 ▼ (-0.02 from last month)
--
--Hallucination Rate: 4.2%
-- - Claims without evidence support: 3.1%
-- - Misrepresented evidence: 1.1%
--
--Action: Prompt engineering review scheduled
--{{/code}}
--
--**3. Evidence Quality Metrics**
--
--**Source Reliability:**
--* Average source quality score (0-1 scale)
--* Distribution of high/medium/low quality sources
--* Publisher track record trends
--
--**Evidence Coverage:**
--* Average number of sources per claim
--* Percentage of claims with ≥2 sources (EFCSN minimum)
--* Geographic diversity of sources
--
--**Display:**
--{{code}}
--Evidence Quality:
--
--Average Sources per Claim: 4.2
--Claims with ≥2 sources: 94% (EFCSN compliant)
--
--Source Quality Distribution:
-- High quality (>0.8): 48%
-- Medium quality (0.5-0.8): 43%
-- Low quality (<0.5): 9%
--
--Geographic Diversity: 23 countries represented
--{{/code}}
--
--**4. Contributor Consensus Metrics** (when human reviewers involved)
--
--**Inter-Rater Reliability (IRR):**
--* **Calculation:** Cohen's Kappa or Fleiss' Kappa for multiple raters
--* **Scale:** 0-1 (higher is better)
--* **Interpretation:**
-- * >0.8: Almost perfect agreement
-- * 0.6-0.8: Substantial agreement
-- * 0.4-0.6: Moderate agreement
-- * <0.4: Poor agreement
--* **Target:** Maintain ≥0.7 (substantial agreement)
--
--**Display:**
--{{code}}
--Contributor Consensus:
--
--Inter-Rater Reliability (IRR): 0.73 (Substantial agreement)
-- - Verdict agreement: 78%
-- - Evidence quality agreement: 71%
-- - Scenario structure agreement: 69%
--
--Cases requiring moderator review: 12
--Moderator override rate: 8%
--{{/code}}
--
-----
--
--==== Quality Dashboard Implementation ====
--
--**Dashboard Location:** `/quality-metrics`
--
--**Update Frequency:**
--* **POC2:** Weekly manual updates
--* **Beta 0:** Daily automated updates
--* **V1.0:** Real-time metrics (updated hourly)
--
--**Dashboard Sections:**
--
--1. **Overview:** Key metrics at a glance
--2. **Verdict Quality:** TIGERScore trends and distributions
--3. **Evidence Analysis:** Source quality and coverage
--4. **AI Performance:** Hallucination rates, AlignScore
--5. **Human Oversight:** Contributor consensus, review rates
--6. **System Health:** Processing times, error rates, uptime
--
--**Example Dashboard Layout:**
--
--{{code}}
--┌─────────────────────────────────────────────────────────────┐
--│ FactHarbor Quality Metrics Last updated: │
--│ Public Dashboard 2 hours ago │
--└─────────────────────────────────────────────────────────────┘
--
--📊 KEY METRICS
--─────────────────────────────────────────────────────────────
--TIGERScore (Verdict Quality): 84.2 ▲ (+2.1)
--AlignScore (Faithfulness): 0.87 ▼ (-0.02)
--Hallucination Rate: 4.2% ✓ (Target: <5%)
--Average Sources per Claim: 4.2 ▲ (+0.3)
--
--📈 TRENDS (30 days)
--─────────────────────────────────────────────────────────────
--[Graph: TIGERScore trending upward]
--[Graph: Hallucination rate declining]
--[Graph: Evidence quality stable]
--
--⚠️ IMPROVEMENT TARGETS
--─────────────────────────────────────────────────────────────
--1. Reduce hallucination rate to <3% (Current: 4.2%)
--2. Increase TIGERScore average to >85 (Current: 84.2)
--3. Maintain IRR >0.75 (Current: 0.73)
--
--📄 DETAILED REPORTS
--─────────────────────────────────────────────────────────────
--• Monthly Quality Report (PDF)
--• Methodology Documentation
--• AKEL Performance Analysis
--• Contributor Agreement Analysis
--
--{{/code}}
--
-----
--
--==== Continuous Improvement Feedback Loop ====
--
--**How Metrics Inform AKEL Improvements:**
--
--1. **Identify Weak Areas:**
-- * Low TIGERScore → Review prompt engineering
-- * High hallucination → Strengthen evidence grounding
-- * Low IRR → Clarify evaluation criteria
--
--2. **A/B Testing Integration:**
-- * Test prompt variations
-- * Measure impact on quality metrics
-- * Deploy winners automatically
--
--3. **Alert Thresholds:**
-- * TIGERScore drops below 75 → Alert team
-- * Hallucination rate exceeds 7% → Pause auto-publishing
-- * IRR below 0.6 → Moderator training needed
--
--4. **Monthly Quality Reviews:**
-- * Analyze trends
-- * Identify systematic issues
-- * Plan prompt improvements
-- * Update AKEL models
--
-----
--
--==== Metric Calculation Details ====
--
--**TIGERScore Implementation:**
--* Reference: https://github.com/TIGER-AI-Lab/TIGERScore
--* Input: Generated verdict + reference verdict (from expert)
--* Output: 0-100 score across 5 dimensions
--* Requires: Test set of expert-reviewed claims (minimum 100)
--
--**AlignScore Implementation:**
--* Reference: https://github.com/yuh-zha/AlignScore
--* Input: Generated verdict + source evidence text
--* Output: 0-1 faithfulness score
--* Calculation: Semantic alignment between claim and evidence
--
--**Source Quality Scoring:**
--* Use existing source reliability database (e.g., NewsGuard, MBFC)
--* Factor in: Publication history, corrections record, transparency
--* Scale: 0-1 (weighted average across sources)
--
-----
--
--==== Integration Points ====
--
--* **NFR11: AKEL Quality Assurance** - Metrics validate quality gate effectiveness
--* **FR49: A/B Testing** - Metrics measure test success
--* **FR11: Audit Trail** - Source of quality data
--* **NFR3: Transparency** - Public metrics build trust
--
--**Acceptance Criteria:**
--
--* ✅ All core metrics implemented and calculating correctly
--* ✅ Dashboard updates daily (Beta 0) or hourly (V1.0)
--* ✅ Alerts trigger when metrics degrade beyond thresholds
--* ✅ Monthly quality report auto-generates
--* ✅ Dashboard is publicly accessible (no login required)
--* ✅ Mobile-responsive dashboard design
--* ✅ Metrics inform quarterly AKEL improvement planning
--
--== 13. Requirements Traceability ==
--
--For full traceability matrix showing which requirements fulfill which user needs, see:
--
--* [[User Needs>>FactHarbor.Specification.Requirements.User Needs.WebHome]] - Section 8 includes comprehensive mapping tables
--
--== 14. Related Pages ==
--
--**Non-Functional Requirements (see Section 9):**
--* [[NFR11 — AKEL Quality Assurance Framework>>#NFR11]]
--* [[NFR12 — Security Controls>>#NFR12]]
--* [[NFR13 — Quality Metrics Transparency>>#NFR13]]
--
--**Other Requirements:**
--* [[User Needs>>FactHarbor.Specification.Requirements.User Needs.WebHome]]
--* [[V1.0 Requirements>>FactHarbor.Specification.Requirements.V10.]]
--* [[Gap Analysis>>FactHarbor.Specification.Requirements.GapAnalysis]]
--
--* **[[User Needs>>FactHarbor.Specification.Requirements.User Needs.WebHome]]** - What users need (drives these requirements)
--* [[Architecture>>FactHarbor.Specification.Architecture.WebHome]] - How requirements are implemented
--* [[Data Model>>FactHarbor.Specification.Data Model.WebHome]] - Data structures supporting requirements
--* [[Workflows>>FactHarbor.Specification.Workflows.WebHome]] - User interaction workflows
--* [[AKEL>>FactHarbor.Specification.AI Knowledge Extraction Layer (AKEL).WebHome]] - AI system fulfilling automation requirements
++== 13. MVP Scope ==
++**Phase 1 (Months 1-3): Read-Only MVP**
++Build:
++* Automated claim analysis
++* Confidence scoring
++* Source evaluation
++* Browse/search interface
++* User flagging system
++**Goal**: Prove AI quality before adding user editing
++**Phase 2 (Months 4-6): User Contributions**
++Add only if needed:
++* Simple editing (Wikipedia-style)
++* Reputation system
++* Basic moderation
++**Phase 3 (Months 7-12): Refinement**
++* Continuous quality improvement
++* Feature additions based on real usage
++* Scale infrastructure
++**Deferred**:
++* Federation (until multiple successful instances exist)
++* Complex contribution workflows (focus on automation)
++* Extensive role hierarchy (keep simple)
++== 14. Success Metrics ==
++**System Quality** (track weekly):
++* Error rate by category (target: -10%/month)
++* Average confidence score (target: increase)
++* Source quality distribution (target: more high-quality)
++* Contradiction detection rate (target: increase)
++**Efficiency** (track monthly):
++* Claims processed per hour (target: increase)
++* Human hours per claim (target: decrease)
++* Automation coverage (target: >90%)
++* Re-work rate (target: <5%)
++**User Satisfaction** (track quarterly):
++* User flag rate (issues found)
++* Correction acceptance rate (flags valid)
++* Return user rate
++* Trust indicators (surveys)
++== 15. Related Pages ==
++* [[Architecture>>FactHarbor.Specification.Architecture.WebHome]]
++* [[Data Model>>FactHarbor.Specification.Data Model.WebHome]]
++* [[Workflows>>FactHarbor.Specification.Workflows.WebHome]]
  * [[Global Rules>>FactHarbor.Organisation.How-We-Work-Together.GlobalRules.WebHome]]
  * [[Privacy Policy>>FactHarbor.Organisation.How-We-Work-Together.Privacy-Policy]]
--
--= V0.9.70 Additional Requirements =
--
--== Functional Requirements (Additional) ==
--
--=== FR44: ClaimReview Schema Implementation ===
--
--**Fulfills:** UN-13 (Cite FactHarbor Verdicts), UN-14 (API Access for Integration), UN-26 (Search Engine Visibility)
--
--**Purpose:** Generate valid ClaimReview structured data for every published analysis to enable Google/Bing search visibility and fact-check discovery.
--
--**Specification:**
--
--==== Component: Schema.org Markup Generator ====
--
--FactHarbor must generate valid ClaimReview structured data following Schema.org specifications for every published claim analysis.
--
--**Required JSON-LD Schema:**
--
--{{code language="json"}}
--{
-- "@context": "https://schema.org",
-- "@type": "ClaimReview",
-- "datePublished": "YYYY-MM-DD",
-- "url": "https://factharbor.org/claims/{claim_id}",
-- "claimReviewed": "The exact claim text",
-- "author": {
-- "@type": "Organization",
-- "name": "FactHarbor",
-- "url": "https://factharbor.org"
-- },
-- "reviewRating": {
-- "@type": "Rating",
-- "ratingValue": "1-5",
-- "bestRating": "5",
-- "worstRating": "1",
-- "alternateName": "FactHarbor likelihood score"
-- },
-- "itemReviewed": {
-- "@type": "Claim",
-- "author": {
-- "@type": "Person",
-- "name": "Claim author if known"
-- },
-- "datePublished": "YYYY-MM-DD if known",
-- "appearance": {
-- "@type": "CreativeWork",
-- "url": "Original claim URL if from article"
-- }
-- }
--}
--{{/code}}
--
--**FactHarbor-Specific Mapping:**
--
--**Likelihood Score to Rating Scale:**
--* 80-100% likelihood → 5 (Highly Supported)
--* 60-79% likelihood → 4 (Supported)
--* 40-59% likelihood → 3 (Mixed/Uncertain)
--* 20-39% likelihood → 2 (Questionable)
--* 0-19% likelihood → 1 (Refuted)
--
--**Multiple Scenarios Handling:**
--* If claim has multiple scenarios with different verdicts, generate **separate ClaimReview** for each scenario
--* Add `disambiguatingDescription` field explaining scenario context
--* Example: "Scenario: If interpreted as referring to 2023 data..."
--
--==== Implementation Requirements ====
--
--1. **Auto-generate** on claim publication
--2. **Embed** in HTML `<head>` section as JSON-LD script
--3. **Validate** against Schema.org validator before publishing
--4. **Submit** to Google Search Console for indexing
--5. **Update** automatically when verdict changes (integrate with FR8: Time Evolution)
--
--==== Integration Points ====
--
--* **FR7: Automated Verdicts** - Source of rating data and claim text
--* **FR8: Time Evolution** - Triggers schema updates when verdicts change
--* **FR11: Audit Trail** - Logs all schema generation and update events
--
--==== Resources ====
--
--* ClaimReview Project: https://www.claimreviewproject.com
--* Schema.org ClaimReview: https://schema.org/ClaimReview
--* Google Fact Check Guidelines: https://developers.google.com/search/docs/appearance/fact-check
--
--**Acceptance Criteria:**
--
--* ✅ Passes Google Structured Data Testing Tool
--* ✅ Appears in Google Fact Check Explorer within 48 hours of publication
--* ✅ Valid JSON-LD syntax (no errors)
--* ✅ All required fields populated with correct data types
--* ✅ Handles multi-scenario claims correctly (separate ClaimReview per scenario)
--
--=== FR45: User Corrections Notification System ===
--
--**Fulfills:** IFCN Principle 5 (Open & Honest Corrections), EFCSN compliance
--
--**Purpose:** When any claim analysis is corrected, notify users who previously viewed the claim to maintain transparency and build trust.
--
--**Specification:**
--
--==== Component: Corrections Visibility Framework ====
--
--**Correction Types:**
--
--1. **Major Correction:** Verdict changes category (e.g., "Supported" → "Refuted")
--2. **Significant Correction:** Likelihood score changes >20%
--3. **Minor Correction:** Evidence additions, source quality updates
--4. **Scenario Addition:** New scenario added to existing claim
--
--==== Notification Mechanisms ====
--
--**1. In-Page Banner:**
--
--Display prominent banner on claim page:
--
--{{code}}
--[!] CORRECTION NOTICE
--This analysis was updated on [DATE]. [View what changed] [Dismiss]
--
--Major changes:
--• Verdict changed from "Likely True (75%)" to "Uncertain (45%)"
--• New contradicting evidence added from [Source]
--• Scenario 2 updated with additional context
--
--[See full correction log]
--{{/code}}
--
--**2. Correction Log Page:**
--
--* Public changelog at `/claims/{id}/corrections`
--* Displays for each correction:
-- * Date/time of correction
-- * What changed (before/after comparison)
-- * Why changed (reason if provided)
-- * Who made change (AKEL auto-update vs. contributor override)
--
--**3. Email Notifications (opt-in):**
--
--* Send to users who bookmarked or shared the claim
--* Subject: "FactHarbor Correction: [Claim title]"
--* Include summary of changes
--* Link to updated analysis
--
--**4. RSS/API Feed:**
--
--* Corrections feed at `/corrections.rss`
--* API endpoint: `GET /api/corrections?since={timestamp}`
--* Enables external monitoring by journalists and researchers
--
--==== Display Rules ====
--
--* Show banner on **ALL pages** displaying the claim (search results, related claims, embeddings)
--* Banner persists for **30 days** after correction
--* **"Corrections" count badge** on claim card
--* **Timestamp** on every verdict: "Last updated: [datetime]"
--
--==== IFCN Compliance Requirements ====
--
--* Corrections policy published at `/corrections-policy`
--* User can report suspected errors via `/report-error/{claim_id}`
--* Link to IFCN complaint process (if FactHarbor becomes signatory)
--* **Scrupulous transparency:** Never silently edit analyses
--
--==== Integration Points ====
--
--* **FR8: Time Evolution** - Triggers corrections when verdicts change
--* **FR11: Audit Trail** - Source of correction data and change history
--* **NFR3: Transparency** - Public correction log demonstrates commitment
--
--**Acceptance Criteria:**
--
--* ✅ Banner appears within 60 seconds of correction
--* ✅ Correction log is permanent and publicly accessible
--* ✅ Email notifications deliver within 5 minutes
--* ✅ RSS feed updates in real-time
--* ✅ Mobile-responsive banner design
--* ✅ Accessible (screen reader compatible)
--
--=== FR46: Image Verification System ===
--
--**Fulfills:** UN-27 (Visual Claim Verification)
--
--**Purpose:** Verify authenticity and context of images shared with claims to detect manipulation, misattribution, and out-of-context usage.
--
--**Specification:**
--
--==== Component: Multi-Method Image Verification ====
--
--**Method 1: Reverse Image Search**
--
--**Purpose:** Find earlier uses of the image to verify context
--
--**Implementation:**
--* Integrate APIs:
-- * **Google Vision AI** (reverse search)
-- * **TinEye** (oldest known uses)
-- * **Bing Visual Search** (broad coverage)
--
--**Process:**
--1. Extract image from claim or user upload
--2. Query multiple reverse search services
--3. Analyze results for:
-- * Earliest known publication
-- * Original context (what was it really showing?)
-- * Publication timeline
-- * Geographic spread
--
--**Output:**
--{{code}}
--Reverse Image Search Results:
--
--Earliest known use: 2019-03-15 (5 years before claim)
--Original context: "Photo from 2019 flooding in Mumbai"
--This claim uses it for: "2024 hurricane damage in Florida"
--
--⚠️ Image is OUT OF CONTEXT
--
--Found in 47 other articles:
--• 2019-03-15: Mumbai floods (original)
--• 2020-07-22: Bangladesh monsoon
--• 2024-10-15: Current claim (misattributed)
--
--[View full timeline]
--{{/code}}
--
-----
--
--**Method 2: AI Manipulation Detection**
--
--**Purpose:** Detect deepfakes, face swaps, and digital alterations
--
--**Implementation:**
--* Integrate detection services:
-- * **Sensity AI** (deepfake detection)
-- * **Reality Defender** (multimodal analysis)
-- * **AWS Rekognition** (face detection inconsistencies)
--
--**Detection Categories:**
--1. **Face Manipulation:**
-- * Deepfake face swaps
-- * Expression manipulation
-- * Identity replacement
--
--2. **Image Manipulation:**
-- * Copy-paste artifacts
-- * Clone stamp detection
-- * Content-aware fill detection
-- * JPEG compression inconsistencies
--
--3. **AI Generation:**
-- * Detect fully AI-generated images
-- * Identify generation artifacts
-- * Check for model signatures
--
--**Confidence Scoring:**
--* **HIGH (80-100%):** Strong evidence of manipulation
--* **MEDIUM (50-79%):** Suspicious artifacts detected
--* **LOW (0-49%):** Minor inconsistencies or inconclusive
--
--**Output:**
--{{code}}
--Manipulation Analysis:
--
--Face Manipulation: LOW RISK (12%)
--Image Editing: MEDIUM RISK (64%)
-- • Clone stamp artifacts detected in sky region
-- • JPEG compression inconsistent between objects
--
--AI Generation: LOW RISK (8%)
--
--⚠️ Possible manipulation detected. Manual review recommended.
--{{/code}}
--
-----
--
--**Method 3: Metadata Analysis (EXIF)**
--
--**Purpose:** Extract technical details that may reveal manipulation or misattribution
--
--**Extracted Data:**
--* **Camera/Device:** Make, model, software
--* **Timestamps:** Original date, modification dates
--* **Location:** GPS coordinates (if present)
--* **Editing History:** Software used, edit count
--* **File Properties:** Resolution, compression, format conversions
--
--**Red Flags:**
--* Metadata completely stripped (suspicious)
--* Timestamp conflicts with claimed date
--* GPS location conflicts with claimed location
--* Multiple edit rounds (hiding something?)
--* Creation date after modification date (impossible)
--
--**Output:**
--{{code}}
--Image Metadata:
--
--Camera: iPhone 14 Pro
--Original date: 2023-08-12 14:32:15
--Location: 40.7128°N, 74.0060°W (New York City)
--Modified: 2024-10-15 08:45:22
--Software: Adobe Photoshop 2024
--
--⚠️ Location conflicts with claim
--Claim says: "Taken in Los Angeles"
--EXIF says: New York City
--
--⚠️ Edited 14 months after capture
--{{/code}}
--
-----
--
--==== Verification Workflow ====
--
--**Automatic Triggers:**
--1. User submits claim with image
--2. Article being analyzed contains images
--3. Social media post includes photos
--
--**Process:**
--1. Extract images from content
--2. Run all 3 verification methods in parallel
--3. Aggregate results into confidence score
--4. Generate human-readable summary
--5. Display prominently in analysis
--
--**Display Integration:**
--
--Show image verification panel in claim analysis:
--
--{{code}}
--📷 IMAGE VERIFICATION
--
--[Image thumbnail]
--
--✅ Reverse Search: Original context verified
--⚠️ Manipulation: Possible editing detected (64% confidence)
--✅ Metadata: Consistent with claim details
--
--Overall Assessment: CAUTION ADVISED
--This image may have been edited. Original context appears accurate.
--
--[View detailed analysis]
--{{/code}}
--
--==== Integration Points ====
--
--* **FR7: Automated Verdicts** - Image verification affects claim credibility
--* **FR4: Analysis Summary** - Image findings included in summary
--* **UN-27: Visual Claim Verification** - Direct fulfillment
--
--==== Cost Considerations ====
--
--**API Costs (estimated per image):**
--* Google Vision AI: $0.001-0.003
--* TinEye: $0.02 (commercial API)
--* Sensity AI: $0.05-0.10
--* AWS Rekognition: $0.001-0.002
--
--**Total per image:** ~$0.07-0.15
--
--**Mitigation Strategies:**
--* Cache results for duplicate images
--* Use free tier quotas where available
--* Prioritize higher-value claims for deep analysis
--* Offer premium verification as paid tier
--
--**Acceptance Criteria:**
--
--* ✅ Reverse image search finds original sources
--* ✅ Manipulation detection accuracy >80% on test dataset
--* ✅ EXIF extraction works for major image formats (JPEG, PNG, HEIC)
--* ✅ Results display within 10 seconds
--* ✅ Mobile-friendly image comparison interface
--* ✅ False positive rate <15%
--
--=== FR47: Archive.org Integration ===
--
--**Importance:** CRITICAL
--**Fulfills:** Evidence persistence, FR5 (Evidence linking)
--
--**Purpose:** Ensure evidence remains accessible even if original sources are deleted.
--
--**Specification:**
--
--**Automatic Archiving:**
--
--When AKEL links evidence:
--1. Check if URL already archived (Wayback Machine API)
--2. If not, submit for archiving (Save Page Now API)
--3. Store both original URL and archive URL
--4. Display both to users
--
--**Archive Display:**
--
--{{code}}
--Evidence Source: [Original URL]
--Archived: [Archive.org URL] (Captured: [date])
--
--[View Original] [View Archive]
--{{/code}}
--
--**Fallback Logic:**
--
--* If original URL unavailable → Auto-redirect to archive
--* If archive unavailable → Display warning
--* If both unavailable → Flag for manual review
--
--**API Integration:**
--
--* Use Wayback Machine Availability API
--* Use Save Page Now API (SPNv2)
--* Rate limiting: 15 requests/minute (Wayback limit)
--
--**Acceptance Criteria:**
--
--* ✅ All evidence URLs auto-archived
--* ✅ Archive links displayed to users
--* ✅ Fallback to archive if original unavailable
--* ✅ API rate limits respected
--* ✅ Archive status visible in evidence display
--
--== Category 4: Community Safety ===== FR48: Contributor Safety Framework ===
--
--**Importance:** CRITICAL
--**Fulfills:** UN-28 (Safe contribution environment)
--
--**Purpose:** Protect contributors from harassment, doxxing, and coordinated attacks.
--
--**Specification:**
--
--**1. Privacy Protection:**
--
--* **Optional Pseudonymity:** Contributors can use pseudonyms
--* **Email Privacy:** Emails never displayed publicly
--* **Profile Privacy:** Contributors control what's public
--* **IP Logging:** Only for abuse prevention, not public
--
--**2. Harassment Prevention:**
--
--* **Automated Toxicity Detection:** Flag abusive comments
--* **Personal Information Detection:** Auto-block doxxing attempts
--* **Coordinated Attack Detection:** Identify brigading patterns
--* **Rapid Response:** Moderator alerts for harassment
--
--**3. Safety Features:**
--
--* **Block Users:** Contributors can block harassers
--* **Private Contributions:** Option to contribute anonymously
--* **Report Harassment:** One-click harassment reporting
--* **Safety Resources:** Links to support resources
--
--**4. Moderator Tools:**
--
--* **Quick Ban:** Immediately block abusers
--* **Pattern Detection:** Identify coordinated attacks
--* **Appeal Process:** Fair review of moderation actions
--* **Escalation:** Serious threats escalated to authorities
--
--**5. Trusted Contributor Protection:**
--
--* **Enhanced Privacy:** Additional protection for high-profile contributors
--* **Verification:** Optional identity verification (not public)
--* **Legal Support:** Resources for contributors facing legal threats
--
--**Acceptance Criteria:**
--
--* ✅ Pseudonyms supported
--* ✅ Toxicity detection active
--* ✅ Doxxing auto-blocked
--* ✅ Harassment reporting functional
--* ✅ Moderator tools implemented
--* ✅ Safety policy published
--
--== Category 5: Continuous Improvement ===== FR49: A/B Testing Framework ===
--
--**Importance:** CRITICAL
--**Fulfills:** Continuous system improvement
--
--**Purpose:** Test and measure improvements to AKEL prompts, algorithms, and workflows.
--
--**Specification:**
--
--**Test Capabilities:**
--
--1. **Prompt Variations:**
-- * Test different claim extraction prompts
-- * Test different verdict generation prompts
-- * Measure: Accuracy, clarity, completeness
--
--2. **Algorithm Variations:**
-- * Test different source scoring algorithms
-- * Test different confidence calculations
-- * Measure: Audit accuracy, user satisfaction
--
--3. **Workflow Variations:**
-- * Test different quality gate thresholds
-- * Test different risk tier assignments
-- * Measure: Publication rate, quality scores
--
--**Implementation:**
--
--* **Traffic Split:** 50/50 or 90/10 splits
--* **Randomization:** Consistent per claim (not per user)
--* **Metrics Collection:** Automatic for all variants
--* **Statistical Significance:** Minimum sample size calculation
--* **Rollout:** Winner promoted to 100% traffic
--
--**A/B Test Workflow:**
--
--{{code}}
--1. Hypothesis: "New prompt improves claim extraction"
--2. Design test: Control vs. Variant
--3. Define metrics: Extraction accuracy, completeness
--4. Run test: 7-14 days, minimum 100 claims each
--5. Analyze results: Statistical significance?
--6. Decision: Deploy winner or iterate
--{{/code}}
--
--**Acceptance Criteria:**
--
--* ✅ A/B testing framework implemented
--* ✅ Can test prompt variations
--* ✅ Can test algorithm variations
--* ✅ Metrics automatically collected
--* ✅ Statistical significance calculated
--* ✅ Results inform system improvements
--
--=== FR54: Evidence Deduplication ===
--
--**Importance:** CRITICAL (POC2/Beta)
--**Fulfills:** Accurate evidence counting, quality metrics
--
--**Purpose:** Avoid counting the same source multiple times when it appears in different forms.
--
--**Specification:**
--
--**Deduplication Logic:**
--
--1. **URL Normalization:**
-- * Remove tracking parameters (?utm_source=...)
-- * Normalize http/https
-- * Normalize www/non-www
-- * Handle redirects
--
--2. **Content Similarity:**
-- * If two sources have >90% text similarity → Same source
-- * If one is subset of other → Same source
-- * Use fuzzy matching for minor differences
--
--3. **Cross-Domain Syndication:**
-- * Detect wire service content (AP, Reuters)
-- * Mark as single source if syndicated
-- * Count original publication only
--
--**Display:**
--
--{{code}}
--Evidence Sources (3 unique, 5 total):
--
--1. Original Article (NYTimes)
-- - Also appeared in: WashPost, Guardian (syndicated)
--
--2. Research Paper (Nature)
--
--3. Official Statement (WHO)
--{{/code}}
--
--**Acceptance Criteria:**
--
--* ✅ URL normalization works
--* ✅ Content similarity detected
--* ✅ Syndicated content identified
--* ✅ Unique vs. total counts accurate
--* ✅ Improves evidence quality metrics
--
--== Additional Requirements (Lower Importance) ===== FR50: OSINT Toolkit Integration ===
--
--**Fulfills:** Advanced media verification
--
--**Purpose:** Integrate open-source intelligence tools for advanced verification.
--
--**Tools to Integrate:**
--* InVID/WeVerify (video verification)
--* Bellingcat toolkit
--* Additional TBD based on V1.0 learnings
--
--=== FR51: Video Verification System ===
--
--**Fulfills:** UN-27 (Visual claims), advanced media verification
--
--**Purpose:** Verify video-based claims.
--
--**Specification:**
--* Keyframe extraction
--* Reverse video search
--* Deepfake detection (AI-powered)
--* Metadata analysis
--* Acoustic signature analysis
--
--=== FR52: Interactive Detection Training ===
--
--**Fulfills:** Media literacy education
--
--**Purpose:** Teach users to identify misinformation.
--
--**Specification:**
--* Interactive tutorials
--* Practice exercises
--* Detection quizzes
--* Gamification elements
--
--=== FR53: Cross-Organizational Sharing ===
--
--**Fulfills:** Collaboration with other fact-checkers
--
--**Purpose:** Share findings with IFCN/EFCSN members.
--
--**Specification:**
--* API for fact-checking organizations
--* Structured data exchange
--* Privacy controls
--* Attribution requirements
--
--== Summary ==
--
--**V1.0 Critical Requirements (Must Have):**
--
--* FR44: ClaimReview Schema ✅
--* FR45: Corrections Notification ✅
--* FR46: Image Verification ✅
--* FR47: Archive.org Integration ✅
--* FR48: Contributor Safety ✅
--* FR49: A/B Testing ✅
--* FR54: Evidence Deduplication ✅
--* NFR11: Quality Assurance Framework ✅
--* NFR12: Security Controls ✅
--* NFR13: Quality Metrics Dashboard ✅
--
--**V1.1+ (Future):**
--
--* FR50: OSINT Integration
--* FR51: Video Verification
--* FR52: Detection Training
--* FR53: Cross-Org Sharing
--
--**Total:** 11 critical requirements for V1.0
--
--=== FR54: Evidence Deduplication ===
--
--**Fulfills:** Accurate evidence counting, quality metrics
--
--**Purpose:** Avoid counting the same source multiple times when it appears in different forms.
--
--**Specification:**
--
--**Deduplication Logic:**
--
--1. **URL Normalization:**
-- * Remove tracking parameters (?utm_source=...)
-- * Normalize http/https
-- * Normalize www/non-www
-- * Handle redirects
--
--2. **Content Similarity:**
-- * If two sources have >90% text similarity → Same source
-- * If one is subset of other → Same source
-- * Use fuzzy matching for minor differences
--
--3. **Cross-Domain Syndication:**
-- * Detect wire service content (AP, Reuters)
-- * Mark as single source if syndicated
-- * Count original publication only
--
--**Display:**
--
--{{code}}
--Evidence Sources (3 unique, 5 total):
--
--1. Original Article (NYTimes)
-- - Also appeared in: WashPost, Guardian (syndicated)
--
--2. Research Paper (Nature)
--
--3. Official Statement (WHO)
--{{/code}}
--
--**Acceptance Criteria:**
--
--* ✅ URL normalization works
--* ✅ Content similarity detected
--* ✅ Syndicated content identified
--* ✅ Unique vs. total counts accurate
--* ✅ Improves evidence quality metrics
--
--== Additional Requirements (Lower Importance) ===== FR7: Automated Verdicts (Enhanced with Quality Gates) ===
--
--**POC1+ Enhancement:**
--
--After AKEL generates verdict, it passes through quality gates:
--
--{{code}}
--Workflow:
--1. Extract claims
-- ↓
--2. [GATE 1] Validate fact-checkable
-- ↓
--3. Generate scenarios
-- ↓
--4. Generate verdicts
-- ↓
--5. [GATE 4] Validate confidence
-- ↓
--6. Display to user
--{{/code}}
--
--**Updated Verdict States:**
--* PUBLISHED
--* INSUFFICIENT_EVIDENCE
--* NON_FACTUAL_CLAIM
--* PROCESSING
--* ERROR
--
--=== FR4: Analysis Summary (Enhanced with Quality Metadata) ===
--
--**POC1+ Enhancement:**
--
--Display quality indicators:
--
--{{code}}
--Analysis Summary:
-- Verifiable Claims: 3/5
-- High Confidence Verdicts: 1
-- Medium Confidence: 2
-- Evidence Sources: 12
-- Avg Source Quality: 0.73
-- Quality Score: 8.5/10
--{{/code}}
--

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