Wiki source code of Data Examples
Version 3.1 by Robert Schaub on 2025/12/12 09:32
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1.1 | 1 | = Data Examples = |
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3.1 | 3 | Illustrative data objects for FactHarbor entities. |
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3.1 | 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.| | ||
| 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).| | ||
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1.1 | 20 | |
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3.1 | 21 | == Automation Summary == |
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1.1 | 22 | |
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3.1 | 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. |