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AI is dramatically lowering the cost of reading papers, writing code, and running experiments. But as research output explodes, telling which results can be trusted keeps getting harder. CiteArk connects the claims in scientific papers with their experimental conditions, execution process, result evidence, and verification records, so researchers and agents can verify claims, reuse experimental results, and build follow-up research on them instead of repeating work. We hope these trustworthy research records will grow into a scientific foundation that researchers, labs, and agents can all build on together.

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Search papers, claims, runs, and users/

RAC is classified as partially compensation-safe for A4, but it has no gating or idempotency and therefore does not address A1-A3. · CiteArk

When Tool Calls Succeed but Workflows Fail: Anomalies at the Agent–Tool Boundary

Not assessedPlan blockedFindingclaim-runtime-rac

RAC is classified as partially compensation-safe for A4, but it has no gating or idempotency and therefore does not address A1-A3.

Source: paper:PDF p. 7, Table 3, RAC row; Markdown block p7-b65

Reported and observed measurements

No structured measurement is attached to this Claim.

Assessments (0)

No immutable Assessment has been published for this Claim yet.

Runs (0)

No execution has been linked to this Claim yet.

Research Plan identity

Claim version: sha256:ee79b4899a6c3eb6a7dbb724faa93ca01f130c2197353c62209f4b8d2e9a6966
Planned experiments: 0
Evidence objects: 0

Assessing partial A4 coverage and the claimed absence of gating/idempotency requires a qualitative, source-by-source mechanism audit under the anomaly definitions. No deterministic rubric is supplied, so the result is retained unresolved rather than inferred from labels.

Machine-readable Claim

Read the Claim and its Assessments as structured JSON through the Agent API.

Open JSON