Dashboard Overview

  • Manuscript List (Homepage)- Displays all manuscripts processed through Alchemist Review, sorted by upload date. Users can search by Manuscript ID or title, and filter by upload date. Role based access control/Permissions determine which journals are visible to the user.
  • Manuscript Digest (Tab)- A consolidated summary view that organizes manuscript data into clear sections for faster analysis. Designed to minimize time spent navigating PDFs.

Digest Sections

  • Paper Type- Classifies the manuscript by category (e.g., research article, review paper).
  • General Summary- A plain-language overview of the manuscript at a “science magazine” level—intended for non-specialists.
  • Advanced Summary- A more technical synopsis tailored for domain experts, highlighting study design and findings in depth.
  • Methods- Outlines primary methods used in the paper, with inline access to AI explanations. Users can hover and select “Ask AI Chat” to learn more about specific techniques.
  • Key Concepts- AI-generated list of major terms and themes in the paper. These may differ from author-provided keywords. (Ongoing model tuning is improving accuracy.)
  • Author Contributions- Summarizes what the authors claim to contribute to the field, drawn directly from the manuscript text.
  • Key Issues & Proposed Remedies- Identifies weaknesses in the research (e.g., methodological gaps) and AI-suggested remedies. Note: may over-flag “lacking state-of-the-art methods”; refinement in progress.
  • Writing Quality & Readability- Analyzes text clarity and flow, flagging issues like run-on sentences or structural confusion.

Citation Evaluation

  • Citation Analysis (Digest Summary)- Summarizes checks from the Citation Evaluation tab—flags missing DOIs, invalid sources, or irrelevant references.
  • Citation Evaluation Tab- Detailed reference-level assessment including:
  • DOI Validity – Confirms correct DOI formatting and matching.
    • Source Validity – Verifies citations link to legitimate publications.
    • Relevance Score – Rates how appropriately each reference supports the paper
    • Retraction Flags – Highlights retracted papers or authors with prior retractions.
    • Severity Filters – Classifies issues as Critical, Minor, or Pass.
    • Interactive Table – Clickable list linking to full references and in-text citations.
  • Author Representation- Analyzes the proportion of self-citations and author repetition—potential signal for citation rings.
  • Journal Representation- Shows how often each journal is cited, helping assess whether references align with journal scope and audience.
  • Recency Analysis- Charts publication dates of cited references, allowing filtering by timeframe (e.g., last 5, 10, or 25 years).

AI Chat

AI Chat Panel – An interactive assistant built into the dashboard for manuscript-level inquiry. It is built on Open Scholar and is not limited to information in the manuscript itself. The chat history is saved per manuscript.

Users can:

  • Ask about methods, data reliability, or conceptual meaning.

  • Access pre-populated prompts via hover icons beside digest items.

  • Retrieve context from manuscript text, digest data, and external sources via Open Scholar.

  • View per-manuscript conversation history for auditability.

Inline Feedback 


 Allows users to rate AI-generated content (Thumbs up/down) and provide qualitative comments (e.g., “too much information,” “irrelevant”). Feedback is reviewed by Hum’s product team regularly.

 

Administrative Functions

Permissions Management – Controls journal access for users; editors may have restricted visibility while staff can access multiple titles.