Changes for page POC Requirements (POC1 & POC2)

Summary

• Page properties (1 modified, 0 added, 0 removed)

Details

Page properties

Content

...	...	@@ -9,9 +9,11 @@
9	9	=== 1.1 What POC Tests ===
10	10
11	11	**Core Question:**
	12	+
12	12	> Can AI automatically extract factual claims from articles and evaluate them with reasonable verdicts?
13	13
14	14	**What we're proving:**
	16	+
15	15	* AI can identify factual claims from text
16	16	* AI can evaluate those claims and produce verdicts
17	17	* Output is comprehensible and useful
...	...	@@ -18,6 +18,7 @@
18	18	* Fully automated approach is viable
19	19
20	20	**What we're NOT testing:**
	23	+
21	21	* Scenario generation (deferred to POC2)
22	22	* Evidence display (deferred to POC2)
23	23	* Production scalability
...	...	@@ -31,6 +31,7 @@
31	31	Scenarios are a core component of the full FactHarbor system (Claims → Scenarios → Evidence → Verdicts), but are **deliberately excluded from POC1**.
32	32
33	33	**Rationale:**
	37	+
34	34	* **POC1 tests:** Can AI extract claims and generate verdicts?
35	35	* **POC2 will add:** Scenario generation and management
36	36	* **Open questions remain:** Should scenarios be separate entities? How are they sequenced with evidence gathering? What's the optimal workflow?
...	...	@@ -42,6 +42,7 @@
42	42	**No Risk:**
43	43
44	44	Scenarios are additive complexity, not foundational. Deferring them to POC2 allows:
	49	+
45	45	* Faster POC1 validation
46	46	* Learning from POC1 to inform scenario design
47	47	* Iterative approach: fail fast if basic AI doesn't work
...	...	@@ -48,14 +48,10 @@
48	48	* Flexibility to adjust scenario architecture based on POC1 insights
49	49
50	50	**Full System Workflow (Future):**
51		-{{code}}
52		-Claims → Scenarios → Evidence → Verdicts
53		-{{/code}}
	56	+{{code}}Claims → Scenarios → Evidence → Verdicts{{/code}}
54	54
55	55	**POC1 Simplified Workflow:**
56		-{{code}}
57		-Claims → Verdicts (scenarios implicit in reasoning)
58		-{{/code}}
	59	+{{code}}Claims → Verdicts (scenarios implicit in reasoning){{/code}}
59	59
60	60	== 2. POC Output Specification ==
61	61
...	...	@@ -66,6 +66,7 @@
66	66	**Length:** 4-6 sentences
67	67
68	68	**Content (Required Elements):**
	70	+
69	69	1. **Article's main thesis/claim** - What is the article trying to argue or prove?
70	70	2. **Claim count and verdicts** - How many claims analyzed, distribution of verdicts
71	71	3. **Central vs. supporting claims** - Which claims are central to the article's argument?
...	...	@@ -75,30 +75,28 @@
75	75	**Critical Innovation:**
76	76
77	77	POC1 tests whether AI can understand that **article credibility ≠ simple average of claim verdicts**. An article might:
	80	+
78	78	* Make accurate supporting facts but draw unsupported conclusions
79	79	* Have one false central claim that invalidates the whole argument
80	80	* Misframe accurate information to mislead
81	81
82	82	**Good Example (Context-Aware):**
83		-{{code}}
84		-This article argues that coffee cures cancer based on its antioxidant
	86	+{{code}}This article argues that coffee cures cancer based on its antioxidant
85	85	content. We analyzed 3 factual claims: 2 about coffee's chemical
86	86	properties are well-supported, but the main causal claim is refuted
87	87	by current evidence. The article confuses correlation with causation.
88	88	Overall assessment: MISLEADING - makes an unsupported medical claim
89		-despite citing some accurate facts.
90		-{{/code}}
	91	+despite citing some accurate facts.{{/code}}
91	91
92	92	**Poor Example (Simple Aggregation - Don't Do This):**
93		-{{code}}
94		-This article makes 3 claims. 2 are well-supported and 1 is refuted.
95		-Overall assessment: mostly accurate (67% accurate).
96		-{{/code}}
	94	+{{code}}This article makes 3 claims. 2 are well-supported and 1 is refuted.
	95	+Overall assessment: mostly accurate (67% accurate).{{/code}}
97	97	↑ This misses that the refuted claim IS the article's main point!
98	98
99	99	**What POC1 Tests:**
100	100
101	101	Can AI identify and assess:
	101	+
102	102	* ✅ The article's main thesis/conclusion?
103	103	* ✅ Which claims are central vs. supporting?
104	104	* ✅ Whether the evidence supports the conclusion?
...	...	@@ -107,6 +107,7 @@
107	107	**If AI Cannot Do This:**
108	108
109	109	That's valuable to learn in POC1! We'll:
	110	+
110	110	* Note as limitation
111	111	* Fall back to simple aggregation with warning
112	112	* Design explicit article-level analysis for POC2
...	...	@@ -117,19 +117,18 @@
117	117	**Format:** Numbered list
118	118	**Quantity:** 3-5 claims
119	119	**Requirements:**
	121	+
120	120	* Factual claims only (not opinions/questions)
121	121	* Clearly stated
122	122	* Automatically extracted by AI
123	123
124	124	**Example:**
125		-{{code}}
126		-CLAIMS IDENTIFIED:
	127	+{{code}}CLAIMS IDENTIFIED:
127	127
128	128	[1] Coffee reduces diabetes risk by 30%
129	129	[2] Coffee improves heart health
130	130	[3] Decaf has same benefits as regular
131		-[4] Coffee prevents Alzheimer's completely
132		-{{/code}}
	132	+[4] Coffee prevents Alzheimer's completely{{/code}}
133	133
134	134	=== 2.3 Component 3: CLAIMS VERDICTS ===
135	135
...	...	@@ -137,6 +137,7 @@
137	137	**Format:** Per claim structure
138	138
139	139	**Required Elements:**
	140	+
140	140	* **Verdict Label:** WELL-SUPPORTED / PARTIALLY SUPPORTED / UNCERTAIN / REFUTED
141	141	* **Confidence Score:** 0-100%
142	142	* **Brief Reasoning:** 1-3 sentences explaining why
...	...	@@ -143,8 +143,7 @@
143	143	* **Risk Tier:** A (High) / B (Medium) / C (Low) - for demonstration
144	144
145	145	**Example:**
146		-{{code}}
147		-VERDICTS:
	147	+{{code}}VERDICTS:
148	148
149	149	[1] WELL-SUPPORTED (85%) [Risk: C]
150	150	Multiple studies confirm 25-30% risk reduction with regular consumption.
...	...	@@ -156,10 +156,10 @@
156	156	Some benefits overlap, but caffeine-related benefits are reduced in decaf.
157	157
158	158	[4] REFUTED (90%) [Risk: B]
159		-No evidence for complete prevention. Claim is significantly overstated.
160		-{{/code}}
	159	+No evidence for complete prevention. Claim is significantly overstated.{{/code}}
161	161
162	162	**Risk Tier Display:**
	162	+
163	163	* **Tier A (Red):** High Risk - Medical/Legal/Safety/Elections
164	164	* **Tier B (Yellow):** Medium Risk - Policy/Science/Causality
165	165	* **Tier C (Green):** Low Risk - Facts/Definitions/History
...	...	@@ -173,13 +173,11 @@
173	173	**Tone:** Neutral (article's position, not FactHarbor's analysis)
174	174
175	175	**Example:**
176		-{{code}}
177		-ARTICLE SUMMARY:
	176	+{{code}}ARTICLE SUMMARY:
178	178
179	179	Health News Today article discusses coffee benefits, citing studies
180	180	on diabetes and Alzheimer's. Author highlights research linking coffee
181		-to disease prevention. Recommends 2-3 cups daily for optimal health.
182		-{{/code}}
	180	+to disease prevention. Recommends 2-3 cups daily for optimal health.{{/code}}
183	183
184	184	=== 2.5 Component 5: USAGE STATISTICS (Cost Tracking) ===
185	185
...	...	@@ -186,6 +186,7 @@
186	186	**What:** LLM usage metrics for cost optimization and scaling decisions
187	187
188	188	**Purpose:**
	187	+
189	189	* Understand cost per analysis
190	190	* Identify optimization opportunities
191	191	* Project costs at scale
...	...	@@ -192,8 +192,7 @@
192	192	* Inform architecture decisions
193	193
194	194	**Display Format:**
195		-{{code}}
196		-USAGE STATISTICS:
	194	+{{code}}USAGE STATISTICS:
197	197	• Article: 2,450 words (12,300 characters)
198	198	• Input tokens: 15,234
199	199	• Output tokens: 892
...	...	@@ -201,17 +201,18 @@
201	201	• Estimated cost: $0.24 USD
202	202	• Response time: 8.3 seconds
203	203	• Cost per claim: $0.048
204		-• Model: claude-sonnet-4-20250514
205		-{{/code}}
	202	+• Model: claude-sonnet-4-20250514{{/code}}
206	206
207	207	**Why This Matters:**
208	208
209	209	At scale, LLM costs are critical:
	207	+
210	210	* 10,000 articles/month ≈ $200-500/month
211	211	* 100,000 articles/month ≈ $2,000-5,000/month
212	212	* Cost optimization can reduce expenses 30-50%
213	213
214	214	**What POC1 Learns:**
	213	+
215	215	* How cost scales with article length
216	216	* Prompt optimization opportunities (caching, compression)
217	217	* Output verbosity tradeoffs
...	...	@@ -219,6 +219,7 @@
219	219	* Article length limits (if needed)
220	220
221	221	**Implementation:**
	221	+
222	222	* Claude API already returns usage data
223	223	* No extra API calls needed
224	224	* Display to user + log for aggregate analysis
...	...	@@ -228,7 +228,8 @@
228	228
229	229	=== 2.6 Total Output Size ===
230	230
231		-**Combined:** ~220-350 words
	231	+**Combined:** 220-350 words
	232	+
232	232	* Analysis Summary (Context-Aware): 60-90 words (4-6 sentences)
233	233	* Claims Identification: 30-50 words
234	234	* Claims Verdicts: 100-150 words
...	...	@@ -243,6 +243,7 @@
243	243	The following are **explicitly excluded** from POC:
244	244
245	245	**Content Features:**
	247	+
246	246	* ❌ Scenarios (deferred to POC2)
247	247	* ❌ Evidence display (supporting/opposing lists)
248	248	* ❌ Source links (clickable references)
...	...	@@ -252,6 +252,7 @@
252	252	* ❌ Risk assessment (shown but not workflow-integrated)
253	253
254	254	**Platform Features:**
	257	+
255	255	* ❌ User accounts / authentication
256	256	* ❌ Saved history
257	257	* ❌ Search functionality
...	...	@@ -261,6 +261,7 @@
261	261	* ❌ Social sharing
262	262
263	263	**Technical Features:**
	267	+
264	264	* ❌ Browser extensions
265	265	* ❌ Mobile apps
266	266	* ❌ API endpoints
...	...	@@ -268,6 +268,7 @@
268	268	* ❌ Export features (PDF, CSV)
269	269
270	270	**Quality Features:**
	275	+
271	271	* ❌ Accessibility (WCAG compliance)
272	272	* ❌ Multilingual support
273	273	* ❌ Mobile optimization
...	...	@@ -274,6 +274,7 @@
274	274	* ❌ Media verification (images/videos)
275	275
276	276	**Production Features:**
	282	+
277	277	* ❌ Security hardening
278	278	* ❌ Privacy compliance (GDPR)
279	279	* ❌ Terms of service
...	...	@@ -287,17 +287,13 @@
287	287	=== 4.1 Architecture Comparison ===
288	288
289	289	**POC Architecture (Simplified):**
290		-{{code}}
291		-User Input → Single AKEL Call → Output Display
292		- (all processing)
293		-{{/code}}
	296	+{{code}}User Input → Single AKEL Call → Output Display
	297	+ (all processing){{/code}}
294	294
295	295	**Full System Architecture:**
296		-{{code}}
297		-User Input → Claim Extractor → Claim Classifier → Scenario Generator
	300	+{{code}}User Input → Claim Extractor → Claim Classifier → Scenario Generator
298	298	→ Evidence Summarizer → Contradiction Detector → Verdict Generator
299		-→ Quality Gates → Publication → Output Display
300		-{{/code}}
	302	+→ Quality Gates → Publication → Output Display{{/code}}
301	301
302	302	**Key Differences:**
303	303
...	...	@@ -313,12 +313,14 @@
313	313	=== 4.2 Workflow Comparison ===
314	314
315	315	**POC1 Workflow:**
	318	+
316	316	1. User submits text/URL
317	317	2. Single AKEL call (all processing in one prompt)
318	318	3. Display results
319		-**Total: 3 steps, ~10-18 seconds**
	322	+**Total: 3 steps, 10-18 seconds**
320	320
321	321	**Full System Workflow:**
	325	+
322	322	1. **Claim Submission** (extraction, normalization, clustering)
323	323	2. **Scenario Building** (definitions, assumptions, boundaries)
324	324	3. **Evidence Handling** (retrieval, assessment, linking)
...	...	@@ -325,7 +325,7 @@
325	325	4. **Verdict Creation** (synthesis, reasoning, approval)
326	326	5. **Public Presentation** (summaries, landscapes, deep dives)
327	327	6. **Time Evolution** (versioning, re-evaluation triggers)
328		-**Total: 6 phases with quality gates, ~10-30 seconds**
	332	+**Total: 6 phases with quality gates, 10-30 seconds**
329	329
330	330	=== 4.3 Why POC is Simplified ===
331	331
...	...	@@ -348,6 +348,7 @@
348	348	=== 4.4 Gap Between POC1 and POC2/Beta ===
349	349
350	350	**What needs to be built for POC2:**
	355	+
351	351	* Scenario generation component
352	352	* Evidence Model structure (full)
353	353	* Scenario-evidence linking
...	...	@@ -355,6 +355,7 @@
355	355	* Truth landscape visualization
356	356
357	357	**What needs to be built for Beta:**
	363	+
358	358	* Multi-component AKEL pipeline
359	359	* Quality gate infrastructure
360	360	* Review workflow system
...	...	@@ -371,6 +371,7 @@
371	371	**Mode:** Mode 2 (AI-Generated, No Prior Human Review)
372	372
373	373	Per FactHarbor Specification Section 11 "POC v1 Behavior":
	380	+
374	374	* Produces public AI-generated output
375	375	* No human approval gate
376	376	* Clear AI-Generated labeling
...	...	@@ -380,8 +380,7 @@
380	380	=== 5.2 User-Facing Labels ===
381	381
382	382	**Primary Label (top of analysis):**
383		-{{code}}
384		-╔════════════════════════════════════════════════════════════╗
	390	+{{code}}╔════════════════════════════════════════════════════════════╗
385	385	║ [AI-GENERATED - POC/DEMO] ║
386	386	║ ║
387	387	║ This analysis was produced entirely by AI and has not ║
...	...	@@ -391,10 +391,10 @@
391	391	║ Review Status: Not Reviewed (Proof-of-Concept) ║
392	392	║ Quality Gates: 4/4 Passed (Simplified) ║
393	393	║ Last Updated: [timestamp] ║
394		-╚════════════════════════════════════════════════════════════╝
395		-{{/code}}
	400	+╚════════════════════════════════════════════════════════════╝{{/code}}
396	396
397	397	**Per-Claim Risk Labels:**
	403	+
398	398	* **[Risk: A]** 🔴 High Risk (Medical/Legal/Safety)
399	399	* **[Risk: B]** 🟡 Medium Risk (Policy/Science)
400	400	* **[Risk: C]** 🟢 Low Risk (Facts/Definitions)
...	...	@@ -402,6 +402,7 @@
402	402	=== 5.3 Display Requirements ===
403	403
404	404	**Must Show:**
	411	+
405	405	* AI-Generated status (prominent)
406	406	* POC/Demo disclaimer
407	407	* Risk tier per claim
...	...	@@ -410,6 +410,7 @@
410	410	* Timestamp
411	411
412	412	**Must NOT Claim:**
	420	+
413	413	* Human review
414	414	* Production quality
415	415	* Medical/legal advice
...	...	@@ -433,6 +433,7 @@
433	433	Per FactHarbor Specification Section 6, all AI-generated content must pass quality gates before publication. POC implements **simplified versions** of the 4 mandatory gates.
434	434
435	435	**Full System Has 4 Gates:**
	444	+
436	436	1. Source Quality
437	437	2. Contradiction Search (MANDATORY)
438	438	3. Uncertainty Quantification
...	...	@@ -439,6 +439,7 @@
439	439	4. Structural Integrity
440	440
441	441	**POC Implements Simplified Versions:**
	451	+
442	442	* Focus on demonstrating concept
443	443	* Basic implementations sufficient
444	444	* Failures displayed to user (not blocking)
...	...	@@ -447,6 +447,7 @@
447	447	=== 6.2 Gate 1: Source Quality (Basic) ===
448	448
449	449	**Full System Requirements:**
	460	+
450	450	* Primary sources identified and accessible
451	451	* Source reliability scored against whitelist
452	452	* Citation completeness verified
...	...	@@ -454,6 +454,7 @@
454	454	* Author credentials validated
455	455
456	456	**POC Implementation:**
	468	+
457	457	* ✅ At least 2 sources found
458	458	* ✅ Sources accessible (URLs valid)
459	459	* ❌ No whitelist checking
...	...	@@ -467,6 +467,7 @@
467	467	=== 6.3 Gate 2: Contradiction Search (Basic) ===
468	468
469	469	**Full System Requirements:**
	482	+
470	470	* Counter-evidence actively searched
471	471	* Reservations and limitations identified
472	472	* Alternative interpretations explored
...	...	@@ -475,6 +475,7 @@
475	475	* Academic literature (supporting AND opposing)
476	476
477	477	**POC Implementation:**
	491	+
478	478	* ✅ Basic search for counter-evidence
479	479	* ✅ Identify obvious contradictions
480	480	* ❌ No comprehensive academic search
...	...	@@ -489,6 +489,7 @@
489	489	=== 6.4 Gate 3: Uncertainty Quantification (Basic) ===
490	490
491	491	**Full System Requirements:**
	506	+
492	492	* Confidence scores calculated for all claims/verdicts
493	493	* Limitations explicitly stated
494	494	* Data gaps identified and disclosed
...	...	@@ -496,6 +496,7 @@
496	496	* Alternative scenarios considered
497	497
498	498	**POC Implementation:**
	514	+
499	499	* ✅ Confidence scores (0-100%)
500	500	* ✅ Basic uncertainty acknowledgment
501	501	* ❌ No detailed limitation disclosure
...	...	@@ -509,6 +509,7 @@
509	509	=== 6.5 Gate 4: Structural Integrity (Basic) ===
510	510
511	511	**Full System Requirements:**
	528	+
512	512	* No hallucinations detected (fact-checking against sources)
513	513	* Logic chain valid and traceable
514	514	* References accessible and verifiable
...	...	@@ -516,6 +516,7 @@
516	516	* Premises clearly stated
517	517
518	518	**POC Implementation:**
	536	+
519	519	* ✅ Basic coherence check
520	520	* ✅ References accessible
521	521	* ❌ No comprehensive hallucination detection
...	...	@@ -529,24 +529,20 @@
529	529	=== 6.6 Quality Gate Display ===
530	530
531	531	**POC shows simplified status:**
532		-{{code}}
533		-Quality Gates: 4/4 Passed (Simplified)
	550	+{{code}}Quality Gates: 4/4 Passed (Simplified)
534	534	✓ Source Quality: 3 sources found
535	535	✓ Contradiction Search: Basic search completed
536	536	✓ Uncertainty: Confidence scores assigned
537		-✓ Structural Integrity: Output coherent
538		-{{/code}}
	554	+✓ Structural Integrity: Output coherent{{/code}}
539	539
540	540	**If any gate fails:**
541		-{{code}}
542		-Quality Gates: 3/4 Passed (Simplified)
	557	+{{code}}Quality Gates: 3/4 Passed (Simplified)
543	543	✓ Source Quality: 3 sources found
544	544	✗ Contradiction Search: Search failed - limited evidence
545	545	✓ Uncertainty: Confidence scores assigned
546	546	✓ Structural Integrity: Output coherent
547	547
548		-Note: This analysis has limited evidence. Use with caution.
549		-{{/code}}
	563	+Note: This analysis has limited evidence. Use with caution.{{/code}}
550	550
551	551	=== 6.7 Simplified vs. Full System ===
552	552
...	...	@@ -563,6 +563,7 @@
563	563	=== 7.1 POC AKEL (Simplified) ===
564	564
565	565	**Implementation:**
	580	+
566	566	* Single Claude API call (Sonnet 4.5)
567	567	* One comprehensive prompt
568	568	* All processing in single request
...	...	@@ -570,8 +570,7 @@
570	570	* No orchestration layer
571	571
572	572	**Prompt Structure:**
573		-{{code}}
574		-Task: Analyze this article and provide:
	588	+{{code}}Task: Analyze this article and provide:
575	575
576	576	1. Extract 3-5 factual claims
577	577	2. For each claim:
...	...	@@ -583,8 +583,7 @@
583	583	4. Generate article summary (3-5 sentences)
584	584	5. Run basic quality checks
585	585
586		-Return as structured JSON.
587		-{{/code}}
	600	+Return as structured JSON.{{/code}}
588	588
589	589	**Processing Time:** 10-18 seconds (estimate)
590	590
...	...	@@ -591,8 +591,7 @@
591	591	=== 7.2 Full System AKEL (Production) ===
592	592
593	593	**Architecture:**
594		-{{code}}
595		-AKEL Orchestrator
	607	+{{code}}AKEL Orchestrator
596	596	├── Claim Extractor
597	597	├── Claim Classifier (with risk tier assignment)
598	598	├── Scenario Generator
...	...	@@ -600,10 +600,10 @@
600	600	├── Contradiction Detector
601	601	├── Quality Gate Validator
602	602	├── Audit Sampling Scheduler
603		-└── Federation Sync Adapter (Release 1.0+)
604		-{{/code}}
	615	+└── Federation Sync Adapter (Release 1.0+){{/code}}
605	605
606	606	**Processing:**
	618	+
607	607	* Parallel processing where possible
608	608	* Separate component calls
609	609	* Quality gates between phases
...	...	@@ -615,6 +615,7 @@
615	615	=== 7.3 Why POC Uses Single Call ===
616	616
617	617	**Advantages:**
	630	+
618	618	* ✅ Simpler to implement
619	619	* ✅ Faster POC development
620	620	* ✅ Easier to debug
...	...	@@ -622,6 +622,7 @@
622	622	* ✅ Good enough for concept validation
623	623
624	624	**Limitations:**
	638	+
625	625	* ❌ No component reusability
626	626	* ❌ No parallel processing
627	627	* ❌ All-or-nothing (can't partially succeed)
...	...	@@ -648,6 +648,7 @@
648	648	**Requirement:** User can submit article for analysis
649	649
650	650	**Functionality:**
	665	+
651	651	* Text input field (paste article text, up to 5000 characters)
652	652	* URL input field (paste article URL)
653	653	* "Analyze" button to trigger processing
...	...	@@ -654,6 +654,7 @@
654	654	* Loading indicator during analysis
655	655
656	656	**Excluded:**
	672	+
657	657	* No user authentication
658	658	* No claim history
659	659	* No search functionality
...	...	@@ -660,6 +660,7 @@
660	660	* No saved templates
661	661
662	662	**Acceptance Criteria:**
	679	+
663	663	* User can paste text from article
664	664	* User can paste URL of article
665	665	* System accepts input and triggers analysis
...	...	@@ -669,6 +669,7 @@
669	669	**Requirement:** AI automatically extracts 3-5 factual claims
670	670
671	671	**Functionality:**
	689	+
672	672	* AI reads article text
673	673	* AI identifies factual claims (not opinions/questions)
674	674	* AI extracts 3-5 most important claims
...	...	@@ -675,6 +675,7 @@
675	675	* System displays numbered list
676	676
677	677	**Critical:** NO MANUAL EDITING ALLOWED
	696	+
678	678	* AI selects which claims to extract
679	679	* AI identifies factual vs. non-factual
680	680	* System processes claims as extracted
...	...	@@ -681,11 +681,13 @@
681	681	* No human curation or correction
682	682
683	683	**Error Handling:**
	703	+
684	684	* If extraction fails: Display error message
685	685	* User can retry with different input
686	686	* No manual intervention to fix extraction
687	687
688	688	**Acceptance Criteria:**
	709	+
689	689	* AI extracts 3-5 claims automatically
690	690	* Claims are factual (not opinions)
691	691	* Claims are clearly stated
...	...	@@ -696,15 +696,17 @@
696	696	**Requirement:** AI automatically generates verdict for each claim
697	697
698	698	**Functionality:**
	720	+
699	699	* For each claim, AI:
700		- * Evaluates claim based on available evidence/knowledge
701		- * Determines verdict: WELL-SUPPORTED / PARTIALLY SUPPORTED / UNCERTAIN / REFUTED
702		- * Assigns confidence score (0-100%)
703		- * Assigns risk tier (A/B/C)
704		- * Writes brief reasoning (1-3 sentences)
	722	+* Evaluates claim based on available evidence/knowledge
	723	+* Determines verdict: WELL-SUPPORTED / PARTIALLY SUPPORTED / UNCERTAIN / REFUTED
	724	+* Assigns confidence score (0-100%)
	725	+* Assigns risk tier (A/B/C)
	726	+* Writes brief reasoning (1-3 sentences)
705	705	* System displays verdict for each claim
706	706
707	707	**Critical:** NO MANUAL EDITING ALLOWED
	730	+
708	708	* AI computes verdicts based on evidence
709	709	* AI generates confidence scores
710	710	* AI writes reasoning
...	...	@@ -711,11 +711,13 @@
711	711	* No human review or adjustment
712	712
713	713	**Error Handling:**
	737	+
714	714	* If verdict generation fails: Display error message
715	715	* User can retry
716	716	* No manual intervention to adjust verdicts
717	717
718	718	**Acceptance Criteria:**
	743	+
719	719	* Each claim has a verdict
720	720	* Confidence score is displayed (0-100%)
721	721	* Risk tier is displayed (A/B/C)
...	...	@@ -728,15 +728,17 @@
728	728	**Requirement:** AI generates brief summary of analysis
729	729
730	730	**Functionality:**
	756	+
731	731	* AI summarizes findings in 3-5 sentences:
732		- * How many claims found
733		- * Distribution of verdicts
734		- * Overall assessment
	758	+* How many claims found
	759	+* Distribution of verdicts
	760	+* Overall assessment
735	735	* System displays at top of results
736	736
737	737	**Critical:** NO MANUAL EDITING ALLOWED
738	738
739	739	**Acceptance Criteria:**
	766	+
740	740	* Summary is coherent
741	741	* Accurately reflects analysis
742	742	* 3-5 sentences
...	...	@@ -747,6 +747,7 @@
747	747	**Requirement:** AI generates brief summary of original article
748	748
749	749	**Functionality:**
	777	+
750	750	* AI summarizes article content (not FactHarbor's analysis)
751	751	* 3-5 sentences
752	752	* System displays
...	...	@@ -756,6 +756,7 @@
756	756	**Critical:** NO MANUAL EDITING ALLOWED
757	757
758	758	**Acceptance Criteria:**
	787	+
759	759	* Summary is neutral (article's position)
760	760	* Accurately reflects article content
761	761	* 3-5 sentences
...	...	@@ -766,6 +766,7 @@
766	766	**Requirement:** Clear labeling of AI-generated content
767	767
768	768	**Functionality:**
	798	+
769	769	* Display Mode 2 publication label
770	770	* Show POC/Demo disclaimer
771	771	* Display risk tiers per claim
...	...	@@ -773,6 +773,7 @@
773	773	* Display timestamp
774	774
775	775	**Acceptance Criteria:**
	806	+
776	776	* Label is prominent and clear
777	777	* User understands this is AI-generated POC output
778	778	* Risk tiers are color-coded
...	...	@@ -783,6 +783,7 @@
783	783	**Requirement:** Execute simplified quality gates
784	784
785	785	**Functionality:**
	817	+
786	786	* Check source quality (basic)
787	787	* Attempt contradiction search (basic)
788	788	* Calculate confidence scores
...	...	@@ -790,6 +790,7 @@
790	790	* Display gate results
791	791
792	792	**Acceptance Criteria:**
	825	+
793	793	* All 4 gates attempted
794	794	* Pass/fail status displayed
795	795	* Failures explained to user
...	...	@@ -804,6 +804,7 @@
804	804	**Critical Rule:** NO MANUAL EDITING AT ANY STAGE
805	805
806	806	**What this means:**
	840	+
807	807	* Claims: AI selects (no human curation)
808	808	* Scenarios: N/A (deferred to POC2)
809	809	* Evidence: AI evaluates (no human selection)
...	...	@@ -811,13 +811,12 @@
811	811	* Summaries: AI writes (no human editing)
812	812
813	813	**Pipeline:**
814		-{{code}}
815		-User Input → AKEL Processing → Output Display
	848	+{{code}}User Input → AKEL Processing → Output Display
816	816	↓
817		- ZERO human editing
818		-{{/code}}
	850	+ ZERO human editing{{/code}}
819	819
820	820	**If AI output is poor:**
	853	+
821	821	* ❌ Do NOT manually fix it
822	822	* ✅ Document the failure
823	823	* ✅ Improve prompts and retry
...	...	@@ -824,6 +824,7 @@
824	824	* ✅ Accept that POC might fail
825	825
826	826	**Why this matters:**
	860	+
827	827	* Tests whether AI can do this without humans
828	828	* Validates scalability (humans can't review every analysis)
829	829	* Honest test of technical feasibility
...	...	@@ -833,16 +833,19 @@
833	833	**Requirement:** Analysis completes in reasonable time
834	834
835	835	**Acceptable Performance:**
	870	+
836	836	* Processing time: 1-5 minutes (acceptable for POC)
837	837	* Display loading indicator to user
838	838	* Show progress if possible ("Extracting claims...", "Generating verdicts...")
839	839
840	840	**Not Required:**
	876	+
841	841	* Production-level speed (< 30 seconds)
842	842	* Optimization for scale
843	843	* Caching
844	844
845	845	**Acceptance Criteria:**
	882	+
846	846	* Analysis completes within 5 minutes
847	847	* User sees loading indicator
848	848	* No timeout errors
...	...	@@ -852,16 +852,19 @@
852	852	**Requirement:** System works for manual testing sessions
853	853
854	854	**Acceptable:**
	892	+
855	855	* Occasional errors (< 20% failure rate)
856	856	* Manual restart if needed
857	857	* Display error messages clearly
858	858
859	859	**Not Required:**
	898	+
860	860	* 99.9% uptime
861	861	* Automatic error recovery
862	862	* Production monitoring
863	863
864	864	**Acceptance Criteria:**
	904	+
865	865	* System works for test demonstrations
866	866	* Errors are handled gracefully
867	867	* User receives clear error messages
...	...	@@ -871,6 +871,7 @@
871	871	**Requirement:** Runs on simple infrastructure
872	872
873	873	**Acceptable:**
	914	+
874	874	* Single machine or simple cloud setup
875	875	* No distributed architecture
876	876	* No load balancing
...	...	@@ -878,6 +878,7 @@
878	878	* Local development environment viable
879	879
880	880	**Not Required:**
	922	+
881	881	* Production infrastructure
882	882	* Multi-region deployment
883	883	* Auto-scaling
...	...	@@ -888,6 +888,7 @@
888	888	**Requirement:** Track and display LLM usage metrics to inform optimization decisions
889	889
890	890	**Must Track:**
	933	+
891	891	* Input tokens (article + prompt)
892	892	* Output tokens (generated analysis)
893	893	* Total tokens
...	...	@@ -896,16 +896,19 @@
896	896	* Article length (words/characters)
897	897
898	898	**Must Display:**
	942	+
899	899	* Usage statistics in UI (Component 5)
900	900	* Cost per analysis
901	901	* Cost per claim extracted
902	902
903	903	**Must Log:**
	948	+
904	904	* Aggregate metrics for analysis
905	905	* Cost distribution by article length
906	906	* Token efficiency trends
907	907
908	908	**Purpose:**
	954	+
909	909	* Understand unit economics
910	910	* Identify optimization opportunities
911	911	* Project costs at scale
...	...	@@ -912,6 +912,7 @@
912	912	* Inform architecture decisions (caching, model selection, etc.)
913	913
914	914	**Acceptance Criteria:**
	961	+
915	915	* ✅ Usage data displayed after each analysis
916	916	* ✅ Metrics logged for aggregate analysis
917	917	* ✅ Cost calculated accurately (Claude API pricing)
...	...	@@ -919,6 +919,7 @@
919	919	* ✅ POC1 report includes cost analysis section
920	920
921	921	**Success Target:**
	969	+
922	922	* Average cost per analysis < $0.05 USD
923	923	* Cost scaling behavior understood (linear/exponential)
924	924	* 2+ optimization opportunities identified
...	...	@@ -930,11 +930,13 @@
930	930	=== 10.1 System Components ===
931	931
932	932	**Frontend:**
	981	+
933	933	* Simple HTML form (text input + URL input + button)
934	934	* Loading indicator
935	935	* Results display page (single page, no tabs/navigation)
936	936
937	937	**Backend:**
	987	+
938	938	* Single API endpoint
939	939	* Calls Claude API (Sonnet 4.5 or latest)
940	940	* Parses response
...	...	@@ -941,10 +941,12 @@
941	941	* Returns JSON to frontend
942	942
943	943	**Data Storage:**
	994	+
944	944	* None required (stateless POC)
945	945	* Optional: Simple file storage or SQLite for demo examples
946	946
947	947	**External Services:**
	999	+
948	948	* Claude API (Anthropic) - required
949	949	* Optional: URL fetch service for article text extraction
950	950
...	...	@@ -977,8 +977,7 @@
977	977	=== 10.3 AI Prompt Strategy ===
978	978
979	979	**Single Comprehensive Prompt:**
980		-{{code}}
981		-Task: Analyze this article and provide:
	1032	+{{code}}Task: Analyze this article and provide:
982	982
983	983	1. Identify the article's main thesis/conclusion
984	984	- What is the article trying to argue or prove?
...	...	@@ -1014,8 +1014,7 @@
1014	1014
1015	1015	7. Write article summary (3-5 sentences: neutral summary of article content)
1016	1016
1017		-Return as structured JSON with quality gate results.
1018		-{{/code}}
	1068	+Return as structured JSON with quality gate results.{{/code}}
1019	1019
1020	1020	**One prompt generates everything.**
1021	1021
...	...	@@ -1026,25 +1026,30 @@
1026	1026	=== 10.4 Technology Stack Suggestions ===
1027	1027
1028	1028	**Frontend:**
	1079	+
1029	1029	* HTML + CSS + JavaScript (minimal framework)
1030	1030	* OR: Next.js (if team prefers)
1031	1031	* Hosted: Local machine OR Vercel/Netlify free tier
1032	1032
1033	1033	**Backend:**
	1085	+
1034	1034	* Python Flask/FastAPI (simple REST API)
1035	1035	* OR: Next.js API routes (if using Next.js)
1036	1036	* Hosted: Local machine OR Railway/Render free tier
1037	1037
1038	1038	**AKEL Integration:**
	1091	+
1039	1039	* Claude API via Anthropic SDK
1040	1040	* Model: Claude Sonnet 4.5 or latest available
1041	1041
1042	1042	**Database:**
	1096	+
1043	1043	* None (stateless acceptable)
1044	1044	* OR: SQLite if want to store demo examples
1045	1045	* OR: JSON files on disk
1046	1046
1047	1047	**Deployment:**
	1102	+
1048	1048	* Local development environment sufficient for POC
1049	1049	* Optional: Deploy to cloud for remote demos
1050	1050
...	...	@@ -1053,6 +1053,7 @@
1053	1053	=== 11.1 Minimum Success (POC Passes) ===
1054	1054
1055	1055	**Required for GO decision:**
	1111	+
1056	1056	* ✅ AI extracts 3-5 factual claims automatically
1057	1057	* ✅ AI provides verdict for each claim automatically
1058	1058	* ✅ Verdicts are reasonable (≥70% make logical sense)
...	...	@@ -1066,6 +1066,7 @@
1066	1066	* ✅ **Optimization opportunities identified** (≥2 potential improvements documented)
1067	1067
1068	1068	**Quality Definition:**
	1125	+
1069	1069	* "Reasonable verdict" = Defensible given general knowledge
1070	1070	* "Coherent summary" = Logically structured, grammatically correct
1071	1071	* "Comprehensible" = Reviewers understand what analysis means
...	...	@@ -1073,6 +1073,7 @@
1073	1073	=== 11.2 POC Fails If ===
1074	1074
1075	1075	**Automatic NO-GO if any of these:**
	1133	+
1076	1076	* ❌ Claim extraction poor (< 60% accuracy - extracts non-claims or misses obvious ones)
1077	1077	* ❌ Verdicts nonsensical (< 60% reasonable - contradictory or random)
1078	1078	* ❌ Output incomprehensible (reviewers can't understand analysis)
...	...	@@ -1084,14 +1084,15 @@
1084	1084	**POC quality expectations:**
1085	1085
1086	1086	|=Component|=Quality Threshold|=Definition
1087		-|Claim Extraction|(% class="success" %)≥70% accuracy(%%) |Identifies obvious factual claims, may miss some edge cases
1088		-|Verdict Logic|(% class="success" %)≥70% defensible(%%) |Verdicts are logical given reasoning provided
1089		-|Reasoning Clarity|(% class="success" %)≥70% clear(%%) |1-3 sentences are understandable and relevant
1090		-|Overall Analysis|(% class="success" %)≥70% useful(%%) |Output helps user understand article claims
	1145	+|Claim Extraction|(% class="success" %)≥70% accuracy |Identifies obvious factual claims, may miss some edge cases
	1146	+|Verdict Logic|(% class="success" %)≥70% defensible |Verdicts are logical given reasoning provided
	1147	+|Reasoning Clarity|(% class="success" %)≥70% clear |1-3 sentences are understandable and relevant
	1148	+|Overall Analysis|(% class="success" %)≥70% useful |Output helps user understand article claims
1091	1091
1092	1092	**Analogy:** "B student" quality (70-80%), not "A+" perfection yet
1093	1093
1094	1094	**Not expecting:**
	1153	+
1095	1095	* 100% accuracy
1096	1096	* Perfect claim coverage
1097	1097	* Comprehensive evidence gathering
...	...	@@ -1099,6 +1099,7 @@
1099	1099	* Production polish
1100	1100
1101	1101	**Expecting:**
	1161	+
1102	1102	* Reasonable claim extraction
1103	1103	* Defensible verdicts
1104	1104	* Understandable reasoning
...	...	@@ -1111,6 +1111,7 @@
1111	1111	**Input:** "Coffee reduces the risk of type 2 diabetes by 30%"
1112	1112
1113	1113	**Expected Output:**
	1174	+
1114	1114	* Extract claim correctly
1115	1115	* Provide verdict: WELL-SUPPORTED or PARTIALLY SUPPORTED
1116	1116	* Confidence: 70-90%
...	...	@@ -1124,6 +1124,7 @@
1124	1124	**Input:** News article URL with multiple claims about politics/health/science
1125	1125
1126	1126	**Expected Output:**
	1188	+
1127	1127	* Extract 3-5 key claims
1128	1128	* Verdict for each (may vary: some supported, some uncertain, some refuted)
1129	1129	* Coherent analysis summary
...	...	@@ -1137,6 +1137,7 @@
1137	1137	**Input:** Article on contested political or scientific topic
1138	1138
1139	1139	**Expected Output:**
	1202	+
1140	1140	* Balanced analysis
1141	1141	* Acknowledges uncertainty where appropriate
1142	1142	* Doesn't overstate confidence
...	...	@@ -1149,6 +1149,7 @@
1149	1149	**Input:** Article with obviously false claim (e.g., "The Earth is flat")
1150	1150
1151	1151	**Expected Output:**
	1215	+
1152	1152	* Extract claim
1153	1153	* Verdict: REFUTED
1154	1154	* High confidence (> 90%)
...	...	@@ -1162,6 +1162,7 @@
1162	1162	**Input:** Article with claim where evidence is genuinely mixed
1163	1163
1164	1164	**Expected Output:**
	1229	+
1165	1165	* Extract claim
1166	1166	* Verdict: UNCERTAIN
1167	1167	* Moderate confidence (40-60%)
...	...	@@ -1174,6 +1174,7 @@
1174	1174	**Input:** Article making medical claims
1175	1175
1176	1176	**Expected Output:**
	1242	+
1177	1177	* Extract claim
1178	1178	* Verdict: [appropriate based on evidence]
1179	1179	* Risk tier: A (High - medical)
...	...	@@ -1191,6 +1191,7 @@
1191	1191	**Option A: GO (Proceed to POC2)**
1192	1192
1193	1193	**Conditions:**
	1260	+
1194	1194	* AI quality ≥70% without manual editing
1195	1195	* Basic claim → verdict pipeline validated
1196	1196	* Internal + advisor feedback positive
...	...	@@ -1199,6 +1199,7 @@
1199	1199	* Clear path to improving AI quality to ≥90%
1200	1200
1201	1201	**Next Steps:**
	1269	+
1202	1202	* Plan POC2 development (add scenarios)
1203	1203	* Design scenario architecture
1204	1204	* Expand to Evidence Model structure
...	...	@@ -1207,6 +1207,7 @@
1207	1207	**Option B: NO-GO (Pivot or Stop)**
1208	1208
1209	1209	**Conditions:**
	1278	+
1210	1210	* AI quality < 60%
1211	1211	* Requires manual editing for most analyses (> 50%)
1212	1212	* Feedback indicates fundamental flaws
...	...	@@ -1214,6 +1214,7 @@
1214	1214	* No clear path to improvement
1215	1215
1216	1216	**Next Steps:**
	1286	+
1217	1217	* **Pivot:** Change to hybrid human-AI approach (accept manual review required)
1218	1218	* **Stop:** Conclude approach not viable, revisit later
1219	1219
...	...	@@ -1220,6 +1220,7 @@
1220	1220	**Option C: ITERATE (Improve POC)**
1221	1221
1222	1222	**Conditions:**
	1293	+
1223	1223	* Concept has merit but execution needs work
1224	1224	* Specific improvements identified
1225	1225	* Addressable with better prompts/approach
...	...	@@ -1226,6 +1226,7 @@
1226	1226	* AI quality between 60-70%
1227	1227
1228	1228	**Next Steps:**
	1300	+
1229	1229	* Improve AI prompts
1230	1230	* Test different approaches
1231	1231	* Re-run POC with improvements
...	...	@@ -1247,6 +1247,7 @@
1247	1247	**Impact:** POC fails
1248	1248
1249	1249	**Mitigation:**
	1322	+
1250	1250	* Extensive prompt engineering and testing
1251	1251	* Use best available AI models (Sonnet 4.5)
1252	1252	* Test with diverse article types
...	...	@@ -1260,6 +1260,7 @@
1260	1260	**Impact:** Works sometimes, fails other times
1261	1261
1262	1262	**Mitigation:**
	1336	+
1263	1263	* Test with 10+ diverse articles
1264	1264	* Measure success rate honestly
1265	1265	* Improve prompts to increase consistency
...	...	@@ -1272,6 +1272,7 @@
1272	1272	**Impact:** Users can't understand analysis
1273	1273
1274	1274	**Mitigation:**
	1349	+
1275	1275	* Create clear explainer document
1276	1276	* Iterate on output format
1277	1277	* Test with non-technical reviewers
...	...	@@ -1285,6 +1285,7 @@
1285	1285	**Impact:** System slow or expensive
1286	1286
1287	1287	**Mitigation:**
	1363	+
1288	1288	* Monitor API usage
1289	1289	* Implement retry logic
1290	1290	* Estimate costs before scaling
...	...	@@ -1297,6 +1297,7 @@
1297	1297	**Impact:** POC becomes too complex
1298	1298
1299	1299	**Mitigation:**
	1376	+
1300	1300	* Strict scope discipline
1301	1301	* Say NO to feature additions
1302	1302	* Keep focus on core question
...	...	@@ -1307,12 +1307,15 @@
1307	1307
1308	1308	=== 15.1 Core Principles ===
1309	1309
1310		-**1. Build Less, Learn More**
	1387	+*
	1388	+**
	1389	+**1. Build Less, Learn More
1311	1311	* Minimum features to test hypothesis
1312	1312	* Don't build unvalidated features
1313	1313	* Focus on core question only
1314	1314
1315	1315	**2. Fail Fast**
	1395	+
1316	1316	* Quick test of hardest part (AI capability)
1317	1317	* Accept that POC might fail
1318	1318	* Better to discover issues early
...	...	@@ -1319,16 +1319,19 @@
1319	1319	* Honest assessment over optimistic hope
1320	1320
1321	1321	**3. Test First, Build Second**
	1402	+
1322	1322	* Validate AI can do this before building platform
1323	1323	* Don't assume it will work
1324	1324	* Let results guide decisions
1325	1325
1326	1326	**4. Automation First**
	1408	+
1327	1327	* No manual editing allowed
1328	1328	* Tests scalability, not just feasibility
1329	1329	* Proves approach can work at scale
1330	1330
1331	1331	**5. Honest Assessment**
	1414	+
1332	1332	* Don't cherry-pick examples
1333	1333	* Don't manually fix bad outputs
1334	1334	* Document failures openly
...	...	@@ -1349,9 +1349,12 @@
1349	1349	❌ Perfectly accurate analysis
1350	1350	❌ Polished user experience
1351	1351
1352		-== 16. Success = Clear Path Forward ==
	1435	+== 16. Success ==
1353	1353
	1437	+ Clear Path Forward ==
	1438	+
1354	1354	**If POC succeeds (≥70% AI quality):**
	1440	+
1355	1355	* ✅ Approach validated
1356	1356	* ✅ Proceed to POC2 (add scenarios)
1357	1357	* ✅ Design full Evidence Model structure
...	...	@@ -1359,6 +1359,7 @@
1359	1359	* ✅ Focus on improving AI quality from 70% → 90%
1360	1360
1361	1361	**If POC fails (< 60% AI quality):**
	1448	+
1362	1362	* ✅ Learn what doesn't work
1363	1363	* ✅ Pivot to different approach
1364	1364	* ✅ OR wait for better AI technology
...	...	@@ -1385,16 +1385,16 @@
1385	1385	**POC1 Implementation:**
1386	1386
1387	1387	* **Primary Provider:** Anthropic Claude API
1388		- * Stage 1: Claude Haiku 4
1389		- * Stage 2: Claude Sonnet 3.5 (cached)
1390		- * Stage 3: Claude Sonnet 3.5
	1475	+* Stage 1: Claude Haiku 4
	1476	+* Stage 2: Claude Sonnet 3.5 (cached)
	1477	+* Stage 3: Claude Sonnet 3.5
1391	1391
1392	1392	* **Provider Interface:** Abstract LLMProvider interface implemented
1393	1393
1394	1394	* **Configuration:** Environment variables for provider selection
1395		- * {{code}}LLM_PRIMARY_PROVIDER=anthropic{{/code}}
1396		- * {{code}}LLM_STAGE1_MODEL=claude-haiku-4{{/code}}
1397		- * {{code}}LLM_STAGE2_MODEL=claude-sonnet-3-5{{/code}}
	1482	+* {{code}}LLM_PRIMARY_PROVIDER=anthropic{{/code}}
	1483	+* {{code}}LLM_STAGE1_MODEL=claude-haiku-4{{/code}}
	1484	+* {{code}}LLM_STAGE2_MODEL=claude-sonnet-3-5{{/code}}
1398	1398
1399	1399	* **Failover:** Basic error handling with cache fallback for Stage 2
1400	1400
...	...	@@ -1414,9 +1414,10 @@
1414	1414	* Cost tracking includes provider name in logs
1415	1415	* Stage 2 falls back to cache on provider failure
1416	1416
1417		-**Implementation:** See [[POC1 API & Schemas Specification>>Test.FactHarbor.Specification.POC.API-and-Schemas.WebHome]] Section 6
	1504	+**Implementation:** See [[POC1 API & Schemas Specification>>Test.FactHarbor V0\.9\.103.Specification.POC.API-and-Schemas.WebHome]] Section 6
1418	1418
1419	1419	**Dependencies:**
	1507	+
1420	1420	* NFR-14 (Main Requirements)
1421	1421	* Design Decision 9
1422	1422	* Architecture Section 2.2
...	...	@@ -1424,5 +1424,3 @@
1424	1424	**Priority:** HIGH (P1)
1425	1425
1426	1426	**Rationale:** Even though POC1 uses single provider, abstraction must be in place from start to avoid costly refactoring later.
1427		-
1428		-