AI for Academic Reading

“READ BEFORE
YOU’RE READ.

A non-decisional signal layer for academic manuscripts.
No summaries. No verdicts. Just visibility.

What CLASR does and doesn’t.

Signals,

not decision.

We surface patterns; you decide.

Behavior,

not summary.

We read claim posture, method, transparency continuity.

Visibility,

not verdict.

We make manuscript risk visible before peer review.

“Manuscripts are not only read for what they claim, but for how they claim.”

— from the CLASR white paper

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Signal Mapping
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See what CLASR sees.

S0 Macro Frame

MAJOR

CLAIM ESCALATION — abstract asserts causal relationship not supported by body.

Argument Chain

T1 FRAMING → METHODS: SUSTAINED

T2 METHODS → RESULTS: SUSTAINED

T3 RESULTS → DISCUSSION: DRIFTED

T4 DISCUSSION → CONCLUSION: SUSTAINED

Profile: PARTIALLY INTACT

Desk-Reject Profile

Scope–Journal Fit
Abstract PostureRISK
Structural Completeness
Language PostureRISK
Integrity & Transparency

Co-occurrence: MODERATE

Sample signal report — 47 signals mapped across 9 sections. No verdicts here. Just visibility.

Who uses CLASR?

Authors

See your manuscript before peer review.

Author Mode

Advisors

Cohort-level visibility for student work.

Advisor Mode

Reviewers

Compressed signals for expert reading.

Reviewer Mode

Institutions

Pre-screen layer for research offices.

Custom Deployment

We don’t train AI models on your manuscripts. Ever.

We help authors, supervisors, and editors see hidden manuscript risks earlier.