Features

Conference Abstract Review

ReviewerZero's Conference Abstract Review integrates with conference submission systems to provide automated integrity screening for abstracts, extended abstracts, and full submissions. Designed for platforms like CTI Meeting Technology's cOASIS, this feature helps program committees identify potential issues at scale.

Integration Overview

Conference Abstract Review adds AI-powered screening to your submission workflow:

  • Automated screening - Process submissions as they arrive
  • Scalable analysis - Handle thousands of abstracts efficiently
  • Structured output - Machine-readable results for your platform
  • Flexible deployment - Works with text submissions and PDF uploads

Review Types

Three review modes support different submission formats and processing requirements.

Abstract Review

For standard conference abstracts (150-500 words). Evaluates:

  • Research objective clarity
  • Methodology appropriateness
  • Significance of findings
  • Writing quality
  • Venue fit (when conference context is provided)

Provides thorough analysis with detailed feedback.

Extended Abstract Review

For multi-page submissions (2-6 pages) submitted as PDFs. Evaluates:

  • Research question clarity and significance
  • Appropriateness of the proposed approach
  • Potential contribution to the field
  • Feasibility of the research plan
  • Presentation quality within page constraints

Calibrated for preliminary research—does not penalize for incomplete methodology or limited results typical of extended abstracts.

Flash Abstract Review

For real-time feedback during the submission process. Provides:

  • Immediate response for interactive author feedback
  • Focus on critical issues only
  • Concise, actionable output

Ideal for giving authors instant feedback as they complete their submission, improving submission quality before final submission.

Comparison

FeatureAbstract ReviewExtended Abstract ReviewFlash Abstract Review
Input formatText (JSON)PDF fileText (JSON)
Typical length150-500 words2-6 pages150-500 words
AI text detectionYesYesNo
Plagiarism detectionYesYesNo
Figure/image analysisNoYesNo
Literature searchYes (full)Yes (full)Yes (lite)
Response typeSynchronousAsynchronousSynchronous
Response time~30 secondsBackground processing~15 seconds
Use caseFinal screeningDocument reviewReal-time author feedback

Response Structure

All review types return structured JSON with consistent fields for easy integration:

Summary

Brief summary of the submission in the reviewer's interpretation—useful for quick triage.

Issues

Problems categorized by priority:

PriorityDescription
HighCritical issues that may warrant rejection
MediumSignificant concerns to flag for reviewers
LowMinor improvements

Each issue includes:

  • title - Short issue identifier
  • description - Detailed explanation
  • impact - Why this matters
  • solution - Suggested fix
  • priority - High, medium, or low

Strengths

Array of key positive aspects identified in the submission.

Additional Comments

Supplementary suggestions beyond issue identification.

Venue Fit

When conference context is provided, includes assessment of how well the submission matches the venue scope and audience:

  • is_good_fit - Boolean indicating overall fit
  • fit_score - Score from 0-100
  • venue_topics - Topics covered by the venue
  • matching_topics - Topics from the abstract that match
  • missing_elements - Elements the abstract is missing for this venue
  • fit_explanation - Detailed explanation

Returns null if no venue is specified.

Novelty Assessment

Evaluates originality based on literature search:

  • novelty_score - Score from 0-100
  • impact_potential - High, medium, or low
  • novelty_explanation - Brief explanation of novelty

Array of related works found via literature search. Each entry includes:

  • title - Paper title
  • authors - Author names
  • year - Publication year
  • venue - Journal or conference name (if available)
  • url - Link to the paper (if available)
  • relevance - Why this work is relevant

AI Text Detection (Full review only)

Detection of AI-generated content:

  • ai_probability - Probability (0-1) that text is AI-generated
  • classification - "human", "ai", or "mixed"
  • headline - Summary of the detection result

Returns null if detection fails. Not included in Flash Abstract Review.

Plagiarism Detection (Full review only)

Detection of potential plagiarism:

  • plagiarism_detected - Boolean indicating if plagiarism was found
  • percent_plagiarized - Percentage of text that appears plagiarized
  • matched_sources - Array of matched source URLs and similarity scores

Returns null if detection fails. Not included in Flash Abstract Review.

Input Parameters

Abstract Review & Flash Abstract Review

ParameterRequiredDescription
abstractYesThe submission text (min 50 characters)
titleNoSubmission title
authorsNoAuthor list with names and affiliations
venueNoTarget conference or journal name for venue fit assessment

Extended Abstract Review

ParameterRequiredDescription
fileYesPDF file of the extended abstract (max 6 pages)
venueNoTarget conference or journal name for venue fit assessment
public_viewNoIf true, make the analysis publicly accessible and return URL
notify_emailNoIf true, send email notification when analysis completes

Integration Patterns

Submission-Time Screening

Run Flash Abstract Review as authors submit to provide immediate feedback, allowing them to improve their abstract before final submission.

Batch Processing

Process accepted submissions through Abstract Review or Extended Abstract Review to flag potential issues for program committee review.

Reviewer Support

Include ReviewerZero analysis in reviewer materials to help reviewers focus on content quality rather than formatting or basic issues.

Venue Context

Providing venue information improves review quality:

  • With venue context - Tailored feedback on scope fit and audience alignment
  • Without venue context - General academic quality assessment

Venue context can include conference name, topics of interest, or call for papers text.