Claim

The AGENT framework used high-throughput experiments and Bayesian optimization to identify thermostable solid-state mRNA-lipid nanoparticle vaccine formulations in six iterations over one month.

Type OBSERVATIONAL · truth-evaluable: yes · status at snapshot: ACTIVE · created seq 25181 · qualifiers {"population":"mRNA-lipid nanoparticle vaccine formulations","time_range":"Six optimization iterations completed within one month"}

a conjunction joins clauses that may be separately evaluable

Referenced 131 times: checked 1, looked up by assistants 0, viewed 89, shared 41. A count of attention, not evidence.

Topics

AI · 1efd24fe

Assessment

Supported

Score: 0.8581 under ledger-default@0.3.0 at snapshot 27745

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

1 independent evidence lineage · review checks 1 of 4 · stability MEDIUM

Main unresolved issue: 2 counted evidence items have no independence review; repeats of one origin may be counted as several coverage:cd9415a3-8277-8066-9379-d385bc5d0ec1

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

Why?

Strongest counted support: AGENT coupled high-throughput experimentation with Bayesian optimization and completed formulation optimization in six iterations within one month. weight 1.800000 evidence

Suppressed as dependent: The excerpt states AGENT couples high-throughput experimentation with Bayesian optimization and completed formulation optimization in six iterations within one month.

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 Unresolved.

Hide calculation

0.8581 under ledger-default@0.3.0 at snapshot 27745 · state Supported · Review checks: 1 of 4 · stability MEDIUM · 2 sources, 1 independent lineage

Model ledger-default@0.3.0 (the default model, not the answer) · snapshot 27745 · trace sha256:fb9b3cb0ca8deddd98e1f22e407b3bdbb136d72c7d1d092f5ebfded657faa728

Last changed at entry seq 25732; 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
f9b7c526 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
3daefbed 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 f9b7c526)

prior 0.50 → log-odds 0.000000 + 1.800000 (the counted weights) = 1.800000 → probability 0.8581

Under neighbouring settings of the same model: 0.7790 to 0.9121, a spread of 0.1331.

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.

“An AI-guided Bayesian-optimization framework identified solid-state mRNA-lipid nanoparticle vaccine formulations that retained bioactivity after warm storage...” · 2 claims · 29 September 2026

Evidence for

AGENT coupled high-throughput experimentation with Bayesian optimization and completed formulation optimization in six iterations within one month.

From Accelerated discovery of thermostable mRNA–lipid nanoparticle vaccines using data-efficient AI Read 2026-09-29 Relevance DIRECT Steps 0 Counted

The primary article directly describes the AI framework and optimization schedule.
The excerpt states AGENT couples high-throughput experimentation with Bayesian optimization and completed formulation optimization in six iterations within one month.

From Accelerated discovery of thermostable mRNA–lipid nanoparticle vaccines using data-efficient AI Read 2026-09-29 Relevance DIRECT Steps 0 Counted

Evidence against

None.

Qualifications

None.

Suppressed as dependent

Evidence	Group	Kept instead
4743025a		f9b7c526

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	f9b7c526, 3daefbed

Summary

Supported. The main support is: AGENT coupled high-throughput experimentation with Bayesian optimization and completed formulation optimization in six iterations within one month. 23e4dfc7

1 further item repeats the same origin and is not independent evidence. 4743025a

Review checks: 1 of 4. coverage:cd9415a3-8277-8066-9379-d385bc5d0ec1

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

Contribution history

seq	event	detail
25181	APPENDED
25182	ACCEPT	AUTOMATIC_AFTER_VALIDATION
25189	LINK_EVIDENCE	by 1efd24fe (accepted)
25197	TASK_RESULT	by 1efd24fe (accepted)

Score trace

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  "links": [
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      "evidence": "4d6db41c-85d9-8600-a8d6-027123e4dfc7",
      "direction": "SUPPORT",
      "magnitude": "1.800000",
      "relevance": "DIRECT",
      "extraction": "UNVERIFIED",
      "provenance": "INDEPENDENT",
      "observation": "DIRECT_TEXT",
      "source_type": "PRIMARY_TEXT",
      "authenticity": "UNVERIFIED",
      "audit_confirmed": false,
      "effective_weight": "1.800000",
      "interpretive_steps": 0
    },
    {
      "kept": "19beb06a-75bd-8048-91d5-6be8f9b7c526",
      "link": "d0f2ddc8-bc37-88bb-bd6e-48343daefbed",
      "group": null,
      "reason": "dependent_strongest_only",
      "edition": "NAMED_OR_UNRELATED",
      "evidence": "8568eb0e-84f2-8f24-96d5-50cc4743025a",
      "direction": "SUPPORT",
      "magnitude": "1.800000",
      "relevance": "DIRECT",
      "extraction": "UNVERIFIED",
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      "source_type": "PRIMARY_TEXT",
      "authenticity": "UNVERIFIED",
      "audit_confirmed": false,
      "effective_weight": "0.000000",
      "interpretive_steps": 0
    }
  ],
  "model": "ledger-default@0.3.0",
  "prior": "0.50",
  "variants": {
    "spread": "0.1331",
    "permissive": "0.9121",
    "conservative": "0.7790"
  },
  "code_hash": "sha256:c61a6fdf35a754a0d7e958df149036a083c0eaeb7d2d2e52704ec32b0c36def7",
  "contested": false,
  "stability": "MEDIUM",
  "claim_type": "OBSERVATIONAL",
  "config_hash": "sha256:86768038080b8ab5233f1e4b7aba10af05b5bb44caa432095150b90e81209809",
  "probability": "0.8581",
  "provisional": true,
  "evidence_sum": "1.800000",
  "snapshot_seq": 25732,
  "prior_log_odds": "0.000000",
  "support_groups": 1,
  "model_dependent": false,
  "review_coverage": "0.25",
  "truth_evaluable": true,
  "assessment_state": "SUPPORTED",
  "review_checklist": {
    "qualifiers_reviewed": {
      "by": [],
      "ok": false
    },
    "opposing_search_done": {
      "by": [],
      "ok": false
    },
    "independence_reviewed": {
      "by": [],
      "ok": false
    },
    "primary_source_reviewed": {
      "by": [
        "19beb06a-75bd-8048-91d5-6be8f9b7c526",
        "d0f2ddc8-bc37-88bb-bd6e-48343daefbed"
      ],
      "ok": true
    }
  },
  "contradict_groups": 0,
  "rounding_boundary": false,
  "posterior_log_odds": "1.800000",
  "not_applicable_reason": null,
  "independence_unreviewed": 2
}