SciReview gives editors a structured, evidence-based pre-review of every manuscript — structure, integrity, similarity, ethics and more — so editorial decisions are faster, fairer and fully traceable.
It never accepts or rejects. Every finding shows its evidence. The editor decides.
Before a manuscript ever reaches reviewers, an editor must judge whether it's complete, original, ethical and ready. Today that happens by hand, under time pressure, with tools that either say nothing or say too much.
Missing ethics statements, prior publication, or structural gaps are often caught only after reviewers have spent their time — or after publication.
Two similar manuscripts can get very different first reads depending on who is on desk that day and how busy the office is.
"AI detectors" and one-click verdicts make claims editors can't verify — and that authors can't fairly answer. Trust needs evidence, not a score.
SciReview runs a manuscript through independent review engines and assembles one editorial brief. Every line traces back to something you can check.
No bare "high similarity detected." Each finding lists the matching evidence, a confidence estimate, and a recommended action you can act on.
When two AI reviewers disagree, SciReview surfaces both positions and recommends a human read — it never quietly picks a winner.
Structure, integrity, similarity, duplicate publication, ethics, reporting guidelines and more — deterministic checks first, AI to explain them.
SciReview recommends; it never accepts or rejects. The decision is yours, recorded with the brief and its full provenance.
Upload the manuscript (DOCX, PDF, TXT). SciReview parses sections, references and metadata.
Deterministic engines run first; interpretive engines add AI judgement on top, only where it helps.
Where models are used, their findings are compared; disagreement is surfaced, never hidden.
Findings become one EditorBrief — evidence, confidence and recommended actions, with provenance.
You review the evidence and make the call. Send to review, request revisions, or return — your decision, logged.
Deterministic engines are reproducible and never call a model. Interpretive engines use AI to explain the evidence. One engine is advisory only — and stays out of the summary by design.
Is this a complete manuscript? Detects every expected section and flags what's missing.
Surfaces possible integrity concerns for a human to confirm — observations, never accusations.
Section-level overlap and source breakdown, with optional Turnitin / iThenticate integration.
Searches Crossref and OpenAlex — and sets aside the authors' own preprints, so you see real matches only.
Publication-readiness of the language — framed as editorial support, never a quality gate.
Surface observations only. No score, never an accusation, and excluded from the summary.
Detects the study type and checks CONSORT, PRISMA, STROBE and other checklists for gaps.
Ethics approval, consent, registration, conflicts, funding and data availability — present or missing.
Statistical review and version-to-reviewer comparison are on the roadmap, flagged honestly as they mature.
Start each manuscript with a structured brief instead of a blank page. Spend your judgement where it matters, not on triage.
Set the review profile, choose which models your journal trusts, and keep screening consistent across the whole editorial team.
Give every title the same evidence-based pre-review, with full provenance and an audit trail for editorial accountability.
Validate references and DOIs before publishing.
Score reference relevance and manuscript scope fit.
Verify DOIs and validate Crossref deposit XML.
Announce new work and grow author visibility.
Editorial pre-review before peer review.
From a clean reference list to a confident editorial decision — SciReview is where the manuscript is read before it ever reaches a reviewer.
No — never, by design. SciReview assembles evidence, confidence and recommendations. Every editorial decision belongs to the editor and is recorded alongside the brief.
No. AI text detection is unreliable and unfairly flags non-native English writing. SciReview's AI-assisted-writing engine produces no score, is clearly advisory, never feeds the summary or recommendation, and must never be used to accuse an author.
Yes. Manuscripts are confidential third-party work. SciReview offers a local-only deployment with no external model calls, and where commercial models are used, only under zero-retention, no-training terms. Every external transmission is logged.
That's your choice. An editor-in-chief enables the providers the journal trusts — for example ChatGPT, Gemini or Claude — or runs none at all. Model names are configuration, never hard-wired.
No. SciReview is a pre-review that helps you decide what deserves to enter peer review. It augments editorial judgement; it does not replace editors or reviewers.
Fairness is a built-in principle. Language quality is framed as editorial support and is never used as a gate, and AI-writing observations are never treated as evidence of wrongdoing.
Register your journal and run your first manuscript through SciReview. See the brief before you assign a single reviewer.