Changes for page Requirements

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

From 4.1 to 5.1 From 7.1 to 7.2

From version 5.1

edited by Robert Schaub
on 2025/12/19 10:23

Change comment: There is no comment for this version

To version 7.1

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

Change comment: Imported from XAR

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@@ -1,5 +1,9 @@
  = 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.**
  **Core Philosophy:** Invest in system improvement, not manual data correction. When AI makes errors, improve the algorithm and re-process automatically.
@@ -139,7 +139,7 @@
  * 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), UN-16 (Review status)
++**User Needs served**: UN-1 (Trust score), UN-9 (Methodology transparency), ~~UN-15 (Evolution timeline - Deferred)~~, UN-16 (Review status)
  === 2.2 Hidden ===
@@ -306,7 +306,7 @@
 . How common is this pattern?
 . Store in ErrorPattern table (improvement queue)
--=== 6.2 Weekly Improvement Cycle ===
++=== 6.2 Continuous Improvement Cycle ===
 . **Review**: Analyze top error patterns
 . **Develop**: Create fix (prompt, model, validation)
@@ -326,7 +326,7 @@
  * Re-work rate
  * Claims processed per hour
--**Goal**: 10% monthly improvement in error rate
++**Goal**: continuous improvement in error rate
  == 7. Automated Quality Monitoring ==
@@ -438,6 +438,12 @@
  ==== 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
@@ -489,72 +489,80 @@
  ==== Visual Example: Article with Highlighted Claims ====
--{{code language="none"}}
--┌─────────────────────────────────────────────────────────────────────────────┐
--│ 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.                                     │
--│                                                                             │
--│ [🟢 Researchers found that Mediterranean diet followers had a 25% lower  │
--│     risk of heart disease compared to control groups]                      │
--│     ↑ 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.                 │
--│                                                                             │
--│ [🟡 Some experts believe this diet can completely prevent heart attacks]  │
--│     ↑ 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.                          │
--│                                                                             │
--│ [🔴 The study proves that saturated fats cause heart disease]             │
--│     ↑ 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.                │
--│                                                                             │
--└─────────────────────────────────────────────────────────────────────────────┘
++(% class="box" %)
++(((
++**Article: "New Study Shows Benefits of Mediterranean Diet"**
--Legend:
--🟢 = Well-supported claim (confidence ≥75%)
--🟡 = Uncertain claim (confidence 40-74%)
--🔴 = Refuted/unsupported claim (confidence <40%)
--Plain text = Non-factual content (context, opinions, recommendations)
--{{/code}}
++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 ====
--{{code language="none"}}
--┌────────────────────────────────────────────────────────────┐
--│ 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 →]                                     │
--└────────────────────────────────────────────────────────────┘
--{{/code}}
++(% 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)
@@ -561,34 +561,41 @@
  * **Red**: Refuted or unsupported claims (confidence <40%, contradicted by evidence)
  * **Gray/Neutral**: Non-factual content (opinions, questions, procedural text)
--==== Interactive Highlighting Example (Table Format) ====
++==== Interactive Highlighting Example (Detailed View) ====
--|=**Article Text**|=**Highlighting**|=**Tooltip Info**
--|(((A recent study published in the Journal of Nutrition has revealed new findings about the Mediterranean diet.)))|Plain text|//No highlighting - context//
--|(((Researchers found that Mediterranean diet followers had a 25% lower risk of heart disease compared to control groups)))|(% style="background-color:#90EE90; padding:5px;" %)**🟢 HIGHLIGHTED**|(((
--**WELL SUPPORTED** • 87% confidence
++(% 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**
--Evidence: Meta-analysis of 12 RCTs confirms 23-28% risk reduction
++Meta-analysis of 12 RCTs confirms 23-28% risk reduction
--[[View Full Analysis→]]
++[[View Full Analysis]]
  )))
--|(((The study, which followed 10,000 participants over five years, showed significant improvements in cardiovascular health markers.)))|Plain text|//No highlighting - methodology//
--|(((Some experts believe this diet can completely prevent heart attacks)))|(% style="background-color:#FFD700; padding:5px;" %)**🟡 HIGHLIGHTED**|(((
--**UNCERTAIN** • 45% confidence
++|(((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**
--Issue: Overstated - evidence shows risk reduction, not prevention
++Overstated - evidence shows risk reduction, not prevention
--[[View Details→]]
++[[View Details]]
  )))
--|(((Dr. Rodriguez recommends incorporating more olive oil, fish, and vegetables into daily meals.)))|Plain text|//No highlighting - recommendation//
--|(((The study proves that saturated fats cause heart disease)))|(% style="background-color:#FFB6C6; padding:5px;" %)**🔴 HIGHLIGHTED**|(((
--**REFUTED** • 15% confidence
++|(((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**
--Issue: Claim not supported by study; correlation ≠ causation
++Claim not supported by study; correlation ≠ causation
--[[View Counter-Evidence→]]
++[[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
@@ -597,11 +597,11 @@
  **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
++ * 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
@@ -703,80 +703,500 @@
  * Continuous integration
  * Comprehensive documentation
--== 10. MVP Scope ==
++=== NFR11: AKEL Quality Assurance Framework ===
--**Phase 1 (Months 1-3): Read-Only MVP**
++**Fulfills:** AI safety, IFCN methodology transparency
--Build:
--* Automated claim analysis
--* Confidence scoring
--* Source evaluation
--* Browse/search interface
--* User flagging system
++**Specification:**
--**Goal**: Prove AI quality before adding user editing
++Multi-layer AI quality gates to detect hallucinations, low-confidence results, and logical inconsistencies.
--**User Needs fulfilled in Phase 1**: UN-1, UN-2, UN-3, UN-4, UN-5, UN-6, UN-7, UN-8, UN-9, UN-12
++==== Quality Gate 1: Claim Extraction Validation ====
--**Phase 2 (Months 4-6): User Contributions**
++**Purpose:** Ensure extracted claims are factual assertions (not opinions/predictions)
--Add only if needed:
--* Simple editing (Wikipedia-style)
--* Reputation system
--* Basic moderation
--* In-article claim highlighting (FR13)
++**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?
--**Additional User Needs fulfilled**: UN-13, UN-17
++**Thresholds:**
++* Factual: Must be "Yes"
++* Opinion markers: <2 hedging phrases
++* Specificity: ≥3 specific elements
--**Phase 3 (Months 7-12): Refinement**
++**Action if Failed:** Flag as "Non-verifiable", do NOT generate verdict
--* Continuous quality improvement
--* Feature additions based on real usage
--* Scale infrastructure
++==== Quality Gate 2: Evidence Relevance Validation ====
--**Additional User Needs fulfilled**: UN-14 (API access), UN-15 (Full evolution tracking)
++**Purpose:** Ensure AI-linked evidence actually relates to claim
--**Deferred**:
--* Federation (until multiple successful instances exist)
--* Complex contribution workflows (focus on automation)
--* Extensive role hierarchy (keep simple)
++**Checks:**
++1. **Semantic Similarity Score:** Evidence vs. claim (embeddings)
++2. **Entity Overlap:** Shared people/places/things?
++3. **Topic Relevance:** Discusses claim subject?
--== 11. Success Metrics ==
++**Thresholds:**
++* Similarity: ≥0.6 (cosine similarity)
++* Entity overlap: ≥1 shared entity
++* Topic relevance: ≥0.5
--**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)
++**Action if Failed:** Discard irrelevant evidence
--**Efficiency** (track monthly):
--* Claims processed per hour (target: increase)
--* Human hours per claim (target: decrease)
--* Automation coverage (target: >90%)
--* Re-work rate (target: <5%)
++==== Quality Gate 3: Scenario Coherence Check ====
--**User Satisfaction** (track quarterly):
--* User flag rate (issues found)
--* Correction acceptance rate (flags valid)
--* Return user rate
--* Trust indicators (surveys)
++**Purpose:** Validate scenario assumptions are logical and complete
--**User Needs Metrics** (track quarterly):
--* UN-1: % users who understand trust scores
--* UN-4: Time to verify social media claim (target: <30s)
--* UN-7: % users who access evidence details
--* UN-8: % users who view multiple scenarios
--* UN-15: % users who check evolution timeline
--* UN-17: % users who enable in-article highlighting; avg. time spent on highlighted vs. non-highlighted articles
++**Checks:**
++1. **Completeness:** All required fields populated
++2. **Internal Consistency:** Assumptions don't contradict
++3. **Distinguishability:** Scenarios meaningfully different
--== 12. Requirements Traceability ==
++**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
--== 13. Related Pages ==
++== 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
@@ -784,3 +784,745 @@
  * [[AKEL>>FactHarbor.Specification.AI Knowledge Extraction Layer (AKEL).WebHome]] - AI system fulfilling automation requirements
  * [[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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