Claim

The study found outbreak risks were typically highest in mosaic landscapes where people and livestock coexist alongside forests and fragmented ecosystems, especially for several vector-borne diseases.

Type OBSERVATIONAL · truth-evaluable: yes · status at snapshot: ACTIVE · created seq 22417

26 words; atomic claims are usually under 25a conjunction joins clauses that may be separately evaluable

Referenced 111 times: checked 2, looked up by assistants 0, viewed 73, shared 36. A count of attention, not evidence.

Topics

Public health · 1efd24fe Wildlife · 1efd24fe

Assessment

Supported

Score: 0.9734 under ledger-default@0.3.0 at snapshot 27745

2 of 4 review checks done · 1 counted · 1 by the author only

2 independent evidence lineages · review checks 1 of 4 · stability HIGH

Main unresolved issue: 4 counted evidence items have no independence review; repeats of one origin may be counted as several coverage:4bc74b75-e7f8-836e-a131-e0b9641965c8

Not yet independently audited.Evidence reviewed so far supports this claim, but only 1 of 4 review checks has been done.A quoted passage from nature.com was not found on the page when Galedra fetched it.

Why?

Strongest counted support: The adjusted analyses report increased outbreak risk with forest cover, fragmentation and livestock density across the relevant disease subsets. weight 1.800000 evidence

Suppressed as dependent: The excerpt directly reports highest outbreak risks in mosaic landscapes and strong shared impacts across several vector-borne diseases.

Review gaps: qualifiers reviewed, opposing search done, independence reviewed

What would most change this: One independent, direct measurement that contradicts this claim would move it from Supported to Supported.

Hide calculation

0.9734 under ledger-default@0.3.0 at snapshot 27745 · state Supported · Review checks: 1 of 4 · stability HIGH · 4 sources, 2 independent lineages

Model ledger-default@0.3.0 (the default model, not the answer) · snapshot 27745 · trace sha256:5ec3dfc4eccdad2a551548c02ddc4792d6472733fe11fa7e6438152f9973a867

Last changed at entry seq 25670; nothing logged since has borne on this claim.

How the number was reached

Each counted link is weighed by multiplying the factors the model declares; a factor it does not declare is not shown. Every factor name below links to what that number means.

Link	Working	Weight	Counted as
d8f2ae96 support	relevance DIRECT 2.0 × observation DIRECT_TEXT 0.9 × interpretation 0 steps, 1 − 0.15 × 0 1.000000 × authenticity UNVERIFIED 1.0 × extraction UNVERIFIED 1.0 × provenance INDEPENDENT 1.0 × edition NAMED_OR_UNRELATED 1	1.800000	0.000000 (dependent strongest only, kept ebc3cd26)
fd45785a support	relevance DIRECT 2.0 × observation DIRECT_TEXT 0.9 × interpretation 0 steps, 1 − 0.15 × 0 1.000000 × authenticity UNVERIFIED 1.0 × extraction UNVERIFIED 1.0 × provenance INDEPENDENT 1.0 × edition NAMED_OR_UNRELATED 1	1.800000	1.800000
ebc3cd26 support	relevance DIRECT 2.0 × observation DIRECT_TEXT 0.9 × interpretation 0 steps, 1 − 0.15 × 0 1.000000 × authenticity UNVERIFIED 1.0 × extraction UNVERIFIED 1.0 × provenance INDEPENDENT 1.0 × edition NAMED_OR_UNRELATED 1	1.800000	1.800000
64e827f5 qualify	relevance DIRECT 2.0 × observation MODEL_OUTPUT 0.0 × interpretation 0 steps, 1 − 0.15 × 0 1.000000 × authenticity UNVERIFIED 1.0 × extraction UNVERIFIED 1.0 × provenance INDEPENDENT 1.0 × edition NAMED_OR_UNRELATED 1	0.000000	0.000000 (non directional)

prior 0.50 → log-odds 0.000000 + 3.600000 (the counted weights) = 3.600000 → probability 0.9734

Under neighbouring settings of the same model: 0.9255 to 0.9908, a spread of 0.0653.

Half-even rounding, six places for weights and four for the probability. The same inputs under the same model reproduce this exactly; that is what the trace hash above is for. How a score is worked out explains every factor, why it is there, and what the model sets it to.

Your view

Registered views

Nobody has registered a view yet.

Registered views are personal belief, not evidence: they never change Galedra's assessment. Affiliations are self-declared and shown only for groups of 5 or more.

Checked as part of

Statements this claim was broken out of. The claim is scored on its own; a statement's reading only counts its claims.

“The study found outbreak risks were typically highest in mosaic landscapes where people and livestock coexist alongside forests and fragmented ecosystems,...” · 1 claim · 29 September 2026
“A global Nature analysis linked emerging-disease outbreak geography to heterogeneous anthropogenic drivers and healthcare-access reporting bias.” · 3 claims · 29 September 2026

Evidence for

The primary abstract reports mosaic landscapes and long-term precipitation declines as shared patterns for several vector-borne diseases.

From The anthropogenic fingerprint on emerging infectious diseases Read 2026-09-29 Relevance DIRECT Steps 0 Counted

Exact abstract landscape result.
The adjusted analyses report increased outbreak risk with forest cover, fragmentation and livestock density across the relevant disease subsets.

From The anthropogenic fingerprint on emerging infectious diseases Read 2026-09-29 Relevance DIRECT Steps 0 Counted

Additional primary-text adjusted-analysis result.
The excerpt directly reports highest outbreak risks in mosaic landscapes and strong shared impacts across several vector-borne diseases.

From The anthropogenic fingerprint on emerging infectious diseases Read 2026-09-29 Relevance DIRECT Steps 0 Counted

Evidence against

None.

Qualifications

The mosaic-landscape finding is a global, presence-only, model-adjusted association across specified diseases and years, with detection bias and pseudo-control limitations.

From The anthropogenic fingerprint on emerging infectious diseases Read 2026-09-29 Relevance DIRECT Steps 0 Counted

Adds disease/event denominators, geography, temporal windows, event definition, vector-borne subset, baseline, and detection/reporting limitations.

Suppressed as dependent

Evidence	Group	Kept instead
71a56b51		ebc3cd26

Inferences

Concluded from

None.

Used as a premise in

None.

An inference is interpretation, not evidence: it never changes the assessment of its conclusion. Each premise is a claim with its own evidence.

Threads

None. Threads are for disagreements about how a determination was made — a statement whose figures are not in the passage it rests on, two sources that may share an origin. Something about the world belongs in the evidence above.

Claim edges

None. Edges are stored and displayed; v0.1 does not propagate probability across them.

Review checklist

Review checks: 1 of 4

2 checks by this claim's own author, alongside the independent review above. 1 QUALIFIER CHECK · 1 EVIDENCE VERIFICATION. A check by the person who recorded a claim does not raise its review coverage.

Check	Done	By
qualifiers reviewed	no
opposing search done	no
independence reviewed	no
primary source reviewed	yes	d8f2ae96, fd45785a, ebc3cd26, 64e827f5

Summary

Supported. The main support is: The adjusted analyses report increased outbreak risk with forest cover, fragmentation and livestock density across the relevant disease subsets. 9269d5ed

1 further item repeats the same origin and is not independent evidence. 71a56b51

Qualifier: The mosaic-landscape finding is a global, presence-only, model-adjusted association across specified diseases and years, with detection bias and pseudo-control limitations. 42a65975

Review checks: 1 of 4. coverage:4bc74b75-e7f8-836e-a131-e0b9641965c8

Generated by stub-v0.1; every sentence cites graph ids.

Contribution history

seq	event	detail
22417	APPENDED
22418	ACCEPT	AUTOMATIC_AFTER_VALIDATION
22433	LINK_EVIDENCE	by 1efd24fe (accepted)
22461	LINK_EVIDENCE	by 1efd24fe (accepted)
24597	TASK_RESULT	by 1efd24fe (accepted)
25669	TASK_RESULT	by 1efd24fe (accepted)

Score trace

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      "group": null,
      "reason": "dependent_strongest_only",
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      "reason": "non_directional",
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  "model": "ledger-default@0.3.0",
  "prior": "0.50",
  "variants": {
    "spread": "0.0653",
    "permissive": "0.9908",
    "conservative": "0.9255"
  },
  "code_hash": "sha256:c61a6fdf35a754a0d7e958df149036a083c0eaeb7d2d2e52704ec32b0c36def7",
  "contested": false,
  "stability": "HIGH",
  "claim_type": "OBSERVATIONAL",
  "config_hash": "sha256:86768038080b8ab5233f1e4b7aba10af05b5bb44caa432095150b90e81209809",
  "probability": "0.9734",
  "provisional": true,
  "evidence_sum": "3.600000",
  "snapshot_seq": 25670,
  "prior_log_odds": "0.000000",
  "support_groups": 2,
  "model_dependent": false,
  "review_coverage": "0.25",
  "truth_evaluable": true,
  "assessment_state": "SUPPORTED",
  "review_checklist": {
    "qualifiers_reviewed": {
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    "opposing_search_done": {
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    "independence_reviewed": {
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    "primary_source_reviewed": {
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      ],
      "ok": true
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  "contradict_groups": 0,
  "rounding_boundary": false,
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  "not_applicable_reason": null,
  "independence_unreviewed": 4
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