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Wiki source code of Data Examples

Last modified by Robert Schaub on 2025/12/24 20:31
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1 = Data Examples =
2
3 The following examples illustrate complete, realistic FactHarbor data objects
4 across Claims, Scenarios, Evidence, ScenarioEvidenceLinks, Verdicts, and
5 Re-evaluation behavior.
6
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
30 (% style="width:100%" %)
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|
41
42 ----
43
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