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1		-{{warning title="Version 0.8x (Delta Update)"}}
	1	+{{warning title="Version 0.8ae (Draft)"}}
2	2	This document describes the **Specification** of FactHarbor. It is a working draft.
3	3	{{/warning}}
4	4
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6	6
7	7	This section defines the technical architecture, data models, and functional requirements of FactHarbor.
8	8
9		-== Core Concepts ==
	9	+== Mission ==
10	10
11		-FactHarbor structures reasoning about claims into transparent, inspectable steps:
	11	+**FactHarbor brings clarity and transparency to a world full of unclear, controversial, and misleading information by shedding light on the context, assumptions, and evidence behind claims — empowering people to better understand and judge wisely.**
12	12
13		-* **Claims and Claim Clusters** – people submit real-world statements; similar phrasings are grouped.
14		-* **Scenarios** – each claim is evaluated under clearly defined contexts (assumptions, definitions, boundaries).
15		-* **Evidence** – sources and data are collected and linked to specific scenarios.
16		-* **Verdicts** – **There is no single verdict for a claim.** Instead, there is a distinct verdict for **each scenario** against which the claim is evaluated.
17		-* **Truth Landscape** – the aggregation of these multiple scenario-dependent verdicts shows where (under which assumptions) a claim is plausible and where it is not.
18		-* **Time Evolution** – all important entities (claims, scenarios, evidence links, verdicts) are versioned.
	13	+== Purpose ==
19	19
	15	+Modern society faces a deep informational crisis:
	16	+* Misinformation spreads faster than corrections.
	17	+* High-quality evidence is buried under noise.
	18	+* Meanings shift depending on context — but this is rarely made explicit.
	19	+* Users lack tools to understand *why* information conflicts.
	20	+* Claims are evaluated without clearly defined assumptions.
	21	+
	22	+FactHarbor introduces structure, transparency, and comparative reasoning. It provides:
	23	+* Multiple valid scenarios for ambiguous claims.
	24	+* Transparent assumptions, definitions, and boundaries.
	25	+* Full evidence provenance.
	26	+* Likelihood-based verdicts (one per scenario).
	27	+* Versioning and temporal change tracking.
	28	+* Hybrid AI–human collaboration.
	29	+
	30	+== Core Concepts ==
	31	+
	32	+* **Claim**: A statement needing structured interpretation.
	33	+* **Scenario**: Definitions, assumptions, boundaries, and context.
	34	+* **Evidence**: Information supporting or contradicting a scenario.
	35	+* **Verdict**: Likelihood estimate based on weighted evidence **for a specific scenario**.
	36	+* **Summary View**: User-facing overview.
	37	+* **AKEL**: AI subsystem for drafting and assistance (human supervised).
	38	+* **Federation**: Decentralized nodes hosting datasets.
	39	+* **Truth Landscape**: The aggregation of multiple scenario-dependent verdicts showing where a claim is plausible.
	40	+* **Time Evolution**: Versioning of all entities allowing historical views.
	41	+
20	20	== Functional Lifecycle ==
21	21
22	22	The system follows a six-step lifecycle:
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24	24	1. **Claim submission**: Automatic extraction and normalisation; Cluster detection.
25	25	2. **Scenario building**: Clarifying definitions and assumptions; AI proposals with human approval.
26	26	3. **Evidence handling**: AI-assisted retrieval; Human assessment of reliability; Explicit scenario linking.
27		-4. **Verdict creation**: AI-generated draft verdicts **per scenario**; Human refinement; Reasoning explanations.
	49	+4. **Verdict creation**: AI-generated draft verdicts; Human refinement; Reasoning explanations.
28	28	5. **Public presentation**: Concise summaries; Truth Landscape comparison; Deep dives.
29	29	6. **Time evolution**: Versioning of all entities; Re-evaluation triggers when evidence changes.
30	30