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Changes for page Data Examples

Last modified by Robert Schaub on 2025/12/24 20:31
From version 5.1
edited by Robert Schaub
on 2025/12/12 19:37
Change comment: Imported from XAR
To version 6.4
edited by Robert Schaub
on 2025/12/24 20:31
Change comment: Update document after refactoring.

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1 -FactHarbor.Specification.WebHome
1 +Archive.FactHarbor V0\.9\.18.Specification.WebHome
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1 1  = Data Examples =
2 2  
3 -Illustrative data objects for FactHarbor entities.
3 +The following examples illustrate complete, realistic FactHarbor data objects
4 +across Claims, Scenarios, Evidence, ScenarioEvidenceLinks, Verdicts, and
5 +Re-evaluation behavior.
4 4  
7 +Each field is annotated with:
8 +
9 +* **[A]** — fully automatable
10 +* **[M]** — AI-draft, human validation needed
11 +* **[H]** — human-only
12 +* **[F]** — federation metadata (optional)
13 +
14 +These examples conform to:
15 +
16 +* Data Model (Ch. 5)
17 +* Workflows (Ch. 6)
18 +* Requirements (Ch. 2)
19 +* Architecture (Ch. 3)
20 +* AKEL (Ch. 4)
21 +
22 +----
23 +
24 += Example A — “Hydrogen cars are more energy efficient than EVs.” =
25 +
26 +A clearly empirical, technical, domain-specific claim.
27 +
28 +== Claim (ClaimID: C_H2EV) ==
29 +
5 5  (% style="width:100%" %)
6 -|=(% style="width:20%" %)Example|=(% style="width:80%" %)Details|
7 -|**A: Hydrogen vs EVs**|**Claim**: "Hydrogen cars are more energy efficient than EVs."
8 -**Type**: Empirical / Technical.
9 -**Scenario**: "Well-to-wheel efficiency, EU grid mix 2020-24".
10 -**Assumptions**: Electrolysis 69%, Fuel cell 55%.
11 -**Evidence**: Peer-reviewed paper (High reliability), EU Dataset (Medium).
12 -**Verdict**: Likelihood 0.10–0.25 (Scenario A). Explanation: EVs are more efficient due to lower conversion losses in this context. Use **Verdict** instead of Truth.|
13 -|**B: Cold Water Exposure**|**Claim**: "Regular cold-water exposure improves health."
14 -**Scenario**: "Short daily immersions in healthy adults".
15 -**Definitions**: < 14°C, > 6 months.
16 -**Verdict**: Likelihood 0.40–0.65 (Scenario B). Some benefits shown, but long-term health impact data is limited.|
17 -|**C: Non-Falsifiable**|**Claim**: "Hillary Clinton communicates with Eleanor Roosevelt."
18 -**Scenario**: Literal paranormal interpretation.
19 -**Verdict**: **Undefined** / Non-evaluable. (Reasoning: Non-falsifiable).|
31 +|=Field|=Value|=Notes
32 +|ClaimID|C_H2EV|
33 +|VersionID|v1|
34 +|Text|“Hydrogen cars are more energy efficient than battery electric vehicles (EVs).”|[H]
35 +|Domain|energy_transport|[A]
36 +|ClaimType|literal|[A]
37 +|Evaluability|empirical|[A]
38 +|SafetyCategory|medium|[A]
39 +|ClusterID|CL_EnergyEff|[A]
40 +|Status|active|
20 20  
21 -== Automation Summary ==
42 +----
22 22  
23 -* **[A] Fully Automatable**: Normalization, Clustering, Metadata extraction.
24 -* **[M] Mixed**: Assumptions, Relevance scoring, Uncertainty factors.
25 -* **[H] Human-Only**: Definitions, Ethical constraints, Final approval.
44 +== Scenario S_H2EV_01 — “Well-to-wheel efficiency, EU grid mix” ==
45 +
46 +(% style="width:100%" %)
47 +|=Field|=Value
48 +|ScenarioID|S_H2EV_01
49 +|VersionID|v1
50 +|ClaimID|C_H2EV
51 +|Definitions|//“Well-to-wheel efficiency” = total chain efficiency.// [H]
52 +|Assumptions|EU 2020–24 grid mix, electrolysis 69%, compression losses 10%, fuel cell 55%. [M]
53 +|ContextBoundary|Europe, 2020–2024 technology|[H]
54 +|EvaluationMethod|Comparative WTW energy analysis|[A]
55 +|SafetyClass|low
56 +|Status|active|
57 +
58 +----
59 +
60 +== Evidence ==
61 +
62 +=== Evidence E1 ===
63 +Peer-reviewed energy-systems paper.
64 +
65 +(% style="width:100%" %)
66 +|=Field|=Value
67 +|EvidenceID|E_H2EV_Paper1
68 +|VersionID|v1
69 +|Type|scientific_paper
70 +|Category|empirical
71 +|Reliability|high
72 +|Provenance|Journal publication + DOI
73 +|ExtractionMethod|AKEL + human verification
74 +|Status|verified|
75 +
76 +=== Evidence E2 ===
77 +Official EU dataset.
78 +
79 +(% style="width:100%" %)
80 +|=Field|=Value
81 +|EvidenceID|E_H2EV_Dataset
82 +|VersionID|v1
83 +|Type|dataset
84 +|Category|empirical
85 +|Reliability|medium
86 +|Provenance|EU Energy Stats 2023
87 +|ExtractionMethod|API import
88 +|Status|verified|
89 +
90 +----
91 +
92 +== ScenarioEvidenceLinks ==
93 +
94 +(% style="width:100%" %)
95 +|=(% style="width:30%" %)Scenario|=(% style="width:40%" %)Evidence|=(% style="width:30%" %)RelevanceScore / Notes
96 +|S_H2EV_01 v1|E_H2EV_Paper1 v1|0.92 [M]
97 +|S_H2EV_01 v1|E_H2EV_Dataset v1|0.77 [M]
98 +
99 +----
100 +
101 +== Verdict ==
102 +
103 +=== Verdict V_H2EV_01 v1 ===
104 +
105 +(% style="width:100%" %)
106 +|=Field|=Value
107 +|VerdictID|V_H2EV_01
108 +|VersionID|v1
109 +|ClaimID|C_H2EV
110 +|ScenarioID|S_H2EV_01
111 +|EvidenceVersionSet|[E_H2EV_Paper1:v1, E_H2EV_Dataset:v1]
112 +|LikelihoodRange|0.10–0.25|
113 +|ExplanationSummary|EVs convert grid electricity to motion more efficiently than hydrogen fuel cell vehicles under EU assumptions.|
114 +|ReasoningChain|Step-by-step efficiency-chain comparison|
115 +|UncertaintyFactors|Variability in grid mix, future electrolysis improvements|
116 +|Status|current|
117 +
118 +----
119 +
120 +== Notes ==
121 +
122 +* Many fields automatable (claim classification, domain, initial scenario structure, metadata extraction).
123 +* Definitions and boundaries require human reasoning.
124 +
125 +----
126 +
127 += Example B — “Regular cold-water exposure (<14°C) for ≥6 months improves health.” =
128 +
129 +A complex lifestyle/health claim requiring careful scenario boundaries.
130 +
131 +== Claim (C_CW_Health) ==
132 +
133 +(% style="width:100%" %)
134 +|=Field|=Value
135 +|Text|“Regular cold-water exposure below 14°C for at least 6 months improves health.”|
136 +|Domain|health_lifestyle|
137 +|ClaimType|literal|
138 +|Evaluability|empirical|
139 +|SafetyCategory|high|
140 +
141 +----
142 +
143 +== Scenario S_CW_01 — “Short daily immersions in healthy adults” ==
144 +
145 +(% style="width:100%" %)
146 +|=Field|=Value
147 +|ScenarioID|S_CW_01
148 +|VersionID|v1
149 +|Definitions|“Regular exposure” = 3–7×/week, 2–4 minutes|
150 +|Assumptions|Healthy adults, no cardiovascular risk|
151 +|ContextBoundary|6+ months, 8–14°C|
152 +|EvaluationMethod|Health outcome comparison|
153 +|SafetyClass|high|
154 +
155 +----
156 +
157 +== Evidence ==
158 +
159 +=== Evidence E1 — Dutch cold-shower RCT ===
160 +
161 +(% style="width:100%" %)
162 +|=Field|=Value
163 +|Type|scientific_paper|
164 +|Category|empirical|
165 +|Reliability|high|
166 +|ExtractionMethod|AKEL + human validation|
167 +
168 +=== Evidence E2 — Meta-analysis on immersion effects ===
169 +
170 +(% style="width:100%" %)
171 +|=Field|=Value
172 +|Category|empirical|
173 +|Reliability|medium|
174 +
175 +----
176 +
177 +== ScenarioEvidenceLinks ==
178 +
179 +(% style="width:100%" %)
180 +|=Scenario|=Evidence|=Score
181 +|S_CW_01|E1|0.82
182 +|S_CW_01|E2|0.75
183 +
184 +----
185 +
186 +== Verdict ==
187 +
188 +(% style="width:100%" %)
189 +|=Field|=Value
190 +|LikelihoodRange|0.40–0.65 (uncertain)|
191 +|ExplanationSummary|Some benefits (mood, perceived recovery), but long-term health improvement unclear.|
192 +|UncertaintyFactors|Small sample sizes, lifestyle confounds|
193 +
194 +----
195 +
196 +== Notes ==
197 +
198 +* Medical ethics → high human involvement.
199 +* AKEL helpful for metadata, summaries, and links.
200 +
201 +----
202 +
203 += Example C — “Hillary Clinton communicates with Eleanor Roosevelt.” =
204 +
205 +A belief/metaphorical/non-falsifiable claim.
206 +
207 +== Claim (C_HC_ER) ==
208 +
209 +(% style="width:100%" %)
210 +|=Field|=Value
211 +|Text|“Hillary Clinton communicates with Eleanor Roosevelt.”|
212 +|Domain|politics_private_beliefs|
213 +|ClaimType|metaphorical|
214 +|Evaluability|non-falsifiable|
215 +|SafetyCategory|low|
216 +
217 +----
218 +
219 +== Scenario S_ER_01 — Literal paranormal interpretation ==
220 +
221 +(% style="width:100%" %)
222 +|=Field|=Value
223 +|Definitions|“Communicate” = literal paranormal communication [H]|
224 +|Assumptions|Paranormal abilities exist [H]|
225 +|EvaluationMethod|Not empirically testable|
226 +|SafetyClass|low|
227 +|Evaluability|non-falsifiable|
228 +
229 +----
230 +
231 +== Evidence ==
232 +
233 +Minimal placeholder:
234 +
235 +(% style="width:100%" %)
236 +|=Field|=Value
237 +|EvidenceID|E_None|
238 +|Type|none|
239 +|Category|none|
240 +|Reliability|low|
241 +
242 +----
243 +
244 +== Verdict ==
245 +
246 +LikelihoodRange: **undefined**
247 +Status: **non-evaluable**
248 +Reasoning: claim is non-falsifiable.
249 +
250 +----
251 +
252 += Example D — “Hillary Clinton is a witch.” =
253 +
254 +Clearly rhetorical/metaphorical.
255 +
256 +== Claim (C_HC_Witch) ==
257 +
258 +(% style="width:100%" %)
259 +|=Field|=Value
260 +|Text|“Hillary Clinton is a witch.”|
261 +|Domain|rhetoric|
262 +|ClaimType|rhetorical|
263 +|Evaluability|non-falsifiable|
264 +|SafetyCategory|low|
265 +
266 +----
267 +
268 +== Scenario S_Witch_01 — Literal interpretation ==
269 +
270 +(% style="width:100%" %)
271 +|=Field|=Value
272 +|Definitions|Supernatural definition of “witch”|
273 +|Assumptions|Supernatural powers exist|
274 +|EvaluationMethod|Non-testable|
275 +|Evaluability|non-falsifiable|
276 +
277 +----
278 +
279 +== Evidence ==
280 +
281 +None required.
282 +
283 +----
284 +
285 +== Verdict ==
286 +
287 +Likelihood: **undefined**
288 +Reasoning: rhetorical, not empirical.
289 +
290 +----
291 +
292 += Automation Summary Across Examples =
293 +
294 +== Fully Automatable [A] ==
295 +* Claim normalization
296 +* Claim clustering
297 +* Evidence metadata extraction
298 +* Initial scenario scaffolding
299 +* Reliability heuristics
300 +* Relevance ranking
301 +* Draft verdicts
302 +* Trigger detection
303 +
304 +== Mixed [M] ==
305 +* Assumptions
306 +* Context boundaries
307 +* Relevance scoring
308 +* Reasoning chain
309 +* Uncertainty factors
310 +
311 +== Human-only [H] ==
312 +* Definitions
313 +* Ethical constraints
314 +* High-risk scenario approval
315 +* Interpretation of meaning
316 +* Final verdict approval