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← All cardsDOSSIER · Academic discovery · SOLID · VERIFIED 2026-06-09
Scite70SolidBenchmark pendingCitation-context and evidence-positioning toolVerified 2026-06-09

Dossier · Academic discovery

Scite

Citation-context and evidence-positioning tool · last verified 2026-06-09

Solid
Academic discovery
Scite
70/100
ROLECitation-context and evidence-positioning tool
Editorial fit
70
Source quality
52
Citation honesty
72
Privacy controls
36
Value for money
68
Speed
70
FREEFree
$20/MOPersonal
CUSTOMInstitutional
SolidVerified 2026-06-09VP·METHOD

VERDICT HISTORY

  • Scite is the citation-context card. It is valuable because it asks a better question than raw citation count: did later papers support, contrast, or merely mention the claim? This pass strengthens the card with Scite’s current Smart Citations, MCP, API, publisher/full-text coverage, privacy-policy, and reference-check caveats. The public recommendation remains gated until label accuracy is benchmarked against actual citing passages.
  • Converted imported Notion research into a full flagship-ready dossier template with metrics, panes, pricing deck, scenarios, benchmark rows, and comparison slices.

EDITOR'S NOTE

Scite is valuable because it asks a better citation question. VerdictPal should still make users read the passage: a Smart Citation label is a lead, not a verdict.

AT A GLANCE

Research platform that analyzes citation contexts and classifies citations as supporting, contrasting, or mentioning, with Smart Citations, Scite Assistant, Reference Check, search, dashboards, alerts, API, MCP, and organization analytics.

Role: Citation-context and evidence-positioning toolCategory: Academic discoverySynthesized

Scite flagship-ready dossier: Citation-context and evidence-positioning tool.

PUBLIC FACTS · vendor & repo

List prices and pay-as-you-go entry points we can cite without running our own bench. Each tile links to a source when possible.

Academic discoverySetVerdictPal card ↗
synthesizedEvidenceQuality gate ↗
7Sources checkedCard sources ↗
2026-06-07Pricing checkedQuality gate ↗

Limits & product surface

Non-price vendor claims — multipliers, caps, and API scope. Detailed matrices live in subscription and SDK sections below.

Primary surface
prosumer-saasCard identity ↗
Modalities
text, dataCard identity ↗
Workflow roles
[object Object], [object Object], [object Object]VerdictPal editorial ↗
Alternatives tracked
Elicit, Consensus, Semantic Scholar, Connected Papers, PubMedVerdictPal comparison set ↗

HOW IT WORKS · agent loop

The public positioning for this product — the loop we score against on VerdictPal.

Start with the wedge

Checking whether later papers support, contrast, or merely mention a claim

Run the representative task

Check 10 focal papers and manually verify sampled support/contrast/mention labels against citing passages.

Check the failure modes

Citation classification can misread nuance

Compare before recommending

Compare against Elicit, Consensus, Semantic Scholar before shipping advice.

METRIC LAB · 16 DIMENSIONS

Click a tile for the editorial note. Color follows score: coral, yellow, mint.

Shape

Avg 71 · 36–100

70Editorial fit

Weighted roll-up across 13 dimensions for Academic discovery; pending desk verification if rescored from public facts.

By group

Fit79
  • Editorial fit70
  • Wedge task fit68
  • Feature depth100
Cost63
  • Free-tier utility67
  • Cost-to-value68
  • Opportunity cost55
Trust72
  • Source grounding72
  • Privacy posture36
  • Failure transparency100
  • Evidence strength52
  • Transparency100
Workflow69
  • Integration reach75
  • Setup friction70
  • Reliability70
  • Competitive position75
  • Data portability55

SEARCH MODES · 4 lenses

One input box, many retrieval postures. Filter by tier.

01Free

Workspace

Workspace path for Scite — verify limits on the live product.

02Pro

Collaboration

Collaboration path for Scite — verify limits on the live product.

03Pro

Automation

Automation path for Scite — verify limits on the live product.

04Max

Admin & billing

Admin & billing path for Scite — verify limits on the live product.

BENCHMARK LEDGER

Public rows are vendor or third-party claims we logged with a date. Desk rows are reserved for VerdictPal self-run results.

MeasureResultSource
Check 10 focal papers and manually verify sampled support/contrast/mention labels against citing passagescorrect label rate, nuance errors, missing context, field coverage, decision impact.PlannedVerdictPal benchmark plan
Upload/check a manuscript bibliography with DOI, non-DOI, policy, and news referencesmatch rate, missed references, false matches, usefulness of warnings, privacy friction.PlannedVerdictPal benchmark plan
Ask ChatGPT/Claude with Scite MCP to answer 10 literature questionscitation support, hallucination reduction, source coverage, admin analytics, setup friction.PlannedVerdictPal benchmark plan
Compare Scite, Semantic Scholar, Google Scholar, and Consensus for 10 contested claimstime to understand evidence position, source quality, label/summary correctness, cost justification.PlannedVerdictPal benchmark plan

PRICING DECK · checked 2026-06-09

Desk pick

Personal

$20

month

  • Verify scite.ai/pricing
  • Verify live regional checkout before publishing procurement advice.

RAW · checked 2026-06-09: Scite’s public pricing page timed out during this pass, so keep exact consumer pricing tied to live verification before publishing. Existing desk notes list Basic / Pro / Organization surfaces; current official pages emphasize organization demos, MCP/API access, and Pro access to patents, clinical trials, and grants in MCP release notes.

RESEARCH LOG · desk notes

What we learned while building this dossier — not vendor copy.

Notion Card pipeline ↗

Notion research pass

Scite is the citation-context card. It is valuable because it asks a better question than raw citation count: did later papers support, contrast, or merely mention the claim? This pass strengthens the card with Scite’s current Smart Citations, MCP, API, publisher/full-text coverage, privacy-policy, and reference-check caveats. The public recommendation remains gated until label accuracy is benchmarked against actual citing passages.

VerdictPal git ↗

Flagship-ready structure

Converted imported research into metrics, panes, scenarios, benchmark rows, comparison notes, and pricing deck.

COMPETITIVE LENS

Where Scite wins for cited research — and where a rival still belongs in the stack.

Scite is stronger when checking whether later papers support, contrast, or merely mention a claim; Elicit may still win for narrower fit, procurement, or specialist depth.

Scite

  • Checking whether later papers support, contrast, or merely mention a claim
  • Researchers evaluating a paper’s citation context beyond raw citation count

Elicit

  • You need the cheapest student research assistant and your library does not license Scite
  • You treat Smart Citation labels as final truth without opening citing passages

UNDER THE HOOD

Vendors named on the product about page — useful for procurement and privacy reviews.

citation context checks
Scite
smart citations in manuscripts
Elicit
literature triage
Consensus

DEEP PANES · 6 LENSES

Editorial lenses only. Subscription and API pricing live in their own sections above.

Lens 01

Positioning

Scite is framed here as Citation-context and evidence-positioning tool. Scite is the citation-context card. It is valuable because it asks a better question than raw citation count: did later papers support, contrast, or merely mention the claim? This pass strengthens the card with Scite’s current Smart Citations, MCP, API, publisher/full-text coverage, privacy-policy, and reference-check caveats. The public recommendation remains gated until label accuracy is benchmarked against actual citing passages.

Checked
2026-06-07
Evidence
synthesized
  • Checking whether later papers support, contrast, or merely mention a claim
  • Researchers evaluating a paper’s citation context beyond raw citation count
  • Literature-review workflows that need citation reports, alerts, Reference Check, and grounded AI answers
  • Institutions connecting Scite to ChatGPT, Claude, or other MCP-compatible AI clients

TEST SCENARIOS · hands-on lab

How we exercised the product. Step through each run before you trust the scores.

Test run

Step 1 of 4

Start from the persona in best-for item 1.

BEST FOR

  • Checking whether later papers support, contrast, or merely mention a claim
  • Researchers evaluating a paper’s citation context beyond raw citation count
  • Literature-review workflows that need citation reports, alerts, Reference Check, and grounded AI answers
  • Institutions connecting Scite to ChatGPT, Claude, or other MCP-compatible AI clients

AVOID IF

  • You need the cheapest student research assistant and your library does not license Scite
  • You treat Smart Citation labels as final truth without opening citing passages
  • Your field has sparse citation coverage or relies heavily on books, policy, non-indexed sources, or references without DOIs
  • You need a full systematic-review workflow rather than citation-context triage

STRENGTHS

  • Smart Citations
  • support/contrast/mention contexts
  • Scite Assistant
  • search
  • dashboards
  • collections
  • reports
  • alerts
  • Reference Check
  • Scite MCP
  • Scite API
  • organization analytics
  • patents/clinical trials/grants in MCP release notes

WEAKNESSES

  • Citation classification can misread nuance
  • Reference Check can miss non-DOI/difficult-format sources
  • News/policy/books may be weakly represented
  • Subscription cost may require library access
  • Citation context does not replace methodological appraisal
  • Uploads/searches create a cloud-processing boundary

HOW IT COULD IMPROVE

  • Citation accuracy needs investment. A citation-verification pass against Semantic Scholar or CrossRef before presenting a source would catch the worst fabrication errors.
  • Citation accuracy needs investment. A citation-verification pass against Semantic Scholar or CrossRef before presenting a source would catch the worst fabrication errors.
  • Institutional policy friction could be reduced with a local/on-prem deployment option, or at minimum with clear data-handling documentation that compliance teams can review without an NDA.
  • Privacy posture scores 36/100, the weakest dimension on this dossier. Addressing this would meaningfully raise the editorial fit.
  • Evidence strength scores 52/100, the weakest dimension on this dossier. Addressing this would meaningfully raise the editorial fit.

EDITORIAL EVIDENCE · 4 ENTRIES

TASK

Check 10 focal papers and manually verify sampled support/contrast/mention labels against citing passages.

Pending.

↳ correct label rate, nuance errors, missing context, field coverage, decision impact.

TASK

Upload/check a manuscript bibliography with DOI, non-DOI, policy, and news references.

Pending.

↳ match rate, missed references, false matches, usefulness of warnings, privacy friction.

TASK

Ask ChatGPT/Claude with Scite MCP to answer 10 literature questions.

Pending.

↳ citation support, hallucination reduction, source coverage, admin analytics, setup friction.

TASK

Compare Scite, Semantic Scholar, Google Scholar, and Consensus for 10 contested claims.

Pending.

↳ time to understand evidence position, source quality, label/summary correctness, cost justification.

PRIVACY DEEP-DIVE · checked 2026-06-09

Scite privacy policy effective 2026-03-26 says it may collect and process personal information through use of its website, products, services, and from academic/scientific publications. Treat searches, uploads, Reference Check, Assistant queries, MCP use, and API calls as cloud-processed unless institution-specific terms say otherwise.

Training on your dataNot stated
EU data residencyNot documented
SOC 2 attestationNot documented
Local-first by defaultCloud only

WORKFLOW ROLES

How this tool fits into a composed research stack:

citation context checkssmart citations in manuscriptsliterature triage

QUALITY GATE · SOLID

Evidence ready
Benchmark pending
  • score-revision 2026-06-09: differentiated from public facts; pending desk verification
  • Flagship-quality promotion 2026-06-04: source-backed dossier promoted; benchmark and public recommendation remain locked until evidence packet is complete.
  • Next action: Run label-accuracy, Reference Check, MCP grounding, and value-test benchmarks.
  • Public recommendation: false
  • evidence-override: Notion source-of-truth sync; evidence remains source-backed until desk benchmark or hands-on pass.
  • Flagship-ready structure generated from Notion deep research and imported git fields on 2026-06-09.

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