CLEAR

Claim-Linked Evidence Analysis and Review

Structural evidence analysis for scientific manuscripts. CLEAR examines whether the experimental controls and design actually support the conclusions being drawn.

Manuscript analysis · Editorial integrity support · Based near Heidelberg
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Even if the data are real, do the experimental controls actually support the conclusion?

Most integrity tools detect image manipulation or text reuse. CLEAR asks a different question.

The approach

Figures first, then claims

CLEAR analyzes figures and methods independently before engaging with author narrative. This structural approach reduces confirmation bias and catches mismatches between what the data shows and what the paper claims.

Extract and link Figure panels are extracted, linked to methods and materials, and the experimental structure of each panel is identified: baseline, tested variables, and readout.
Cross-reference materials Listed reagents are checked against presented panels. Antibodies or materials that were purchased but never appear in any figure are flagged.
Map claims to evidence Each claim in the Results section is linked to its supporting panels, creating an auditable claim-to-evidence chain.
Generate rival hypotheses Mechanistically grounded alternative explanations are generated for each panel where the experimental design leaves room for competing interpretations.
Evaluate control sufficiency For each claim, CLEAR assesses whether the controls can discriminate between the authors' interpretation and plausible alternatives.
Structured verdicts

What CLEAR reports

Each linked claim receives one of three structured verdicts, delivered as a self-contained HTML report readable without technical setup.

Full CLEAR

Evaluated against alternatives

The claim is linked to panels where specific rival hypotheses were generated. The report shows whether the experimental design can distinguish the authors' interpretation from each alternative.

CLEAR Lite

Structurally consistent

No specific alternative hypotheses were identified for these panels. The data structure is consistent with the claim. Not the same as confirmed.

Blocked

Baseline too ambiguous

The experimental baseline could not be resolved with enough confidence for formal evaluation. CLEAR reports this honestly rather than forcing a verdict.

The archipelago

Nature, rigor, and perspective

The Swedish archipelago is where I reset, observe, and reconnect with the patterns that inspire my scientific work.

Archipelago at dusk Sunset over the archipelago Archipelago evening light Archipelago sunset reflection
Dr. Asa Hidmark
About

Dr. Asa Hidmark

Biologist with two decades in immunology, from bench work at Scripps, Karolinska, and DKFZ to building CLEAR. I understand both the science and the systems that evaluate it.

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