Medical-research-skills journal-skills

Source: https://github.com/aipoch/medical-research-skills

When to Use

• You have a manuscript title/abstract and need a shortlist of suitable journals to submit to.
• You want evidence-based journal matching using similar PubMed literature and journal distribution statistics.
• You need to compare candidate journals by scope fit, open access requirements, and review/publication timelines.
• You must provide a clear matching rationale (why each journal fits) for internal review or co-author alignment.
• You are planning a submission strategy (primary target + backups) and want to highlight risks and alternatives.

Key Features

• Topic- and abstract-driven journal recommendation workflow.
• PubMed-based similar literature search and journal frequency distribution compilation.
• Candidate journal screening using scope, policy constraints (e.g., OA), and practical considerations (e.g., review cycle).
• Structured recommendation output with rationale, risks, and backup options.
• Reusable CSV template for consistent reporting.

Dependencies

• Python 3.9+ (recommended)
• PubMed E-utilities access (NCBI)

  • EMAIL

    required (per NCBI policy)

  • API_KEY

    optional (recommended for higher rate limits)

Example Usage

1) Prepare inputs

Have the manuscript title and abstract ready.

2) Configure the script

Open

scripts/pubmed_journal_recommender.py

and set the

CONFIG

values:

• EMAIL

  : your email (required)

• API_KEY

  : your NCBI API key (optional)
• Output directory (if the script supports/requests it)

3) Run the recommender

python scripts/pubmed_journal_recommender.py

When prompted, paste the manuscript title and abstract. The script will query PubMed for similar records and produce journal statistics.

4) Produce a structured recommendation table

Use the template below to standardize the final output:

• Template:

  assets/journal_recommendation_template.csv

Fill it with:

• Candidate journals (from the script’s distribution + domain knowledge)
• Matching rationale (scope fit + audience + similarity evidence)
• Constraints (OA, policies)
• Practical notes (review cycle, risks)
• Primary target and backup options

5) Follow the checklist and formatting guidance

For recommended output formats, checklists, and key points, see:

• references/guide.md

Implementation Details

Workflow Overview

1. Topic and Scope Definition

   • Identify the research field, subfield, and intended readership.
   • Confirm journal type preferences and constraints (e.g., OA mandates).

2. Similar Literature Analysis (PubMed)

   • Use the manuscript title/abstract to retrieve similar PubMed records.
   • Aggregate results by journal to compute a distribution (e.g., counts per journal).
   • Prioritize journals that appear frequently among highly relevant records.

3. Journal Screening

   • Cross-check each candidate against:
     • Journal scope/aims
     • Policy requirements (OA, data availability, ethics)
     • Review/publication timelines (if available)
   • Remove journals that are out-of-scope or non-compliant.

4. Recommendation Output

   • Provide a ranked list with:
     • Fit rationale (topic alignment + similarity evidence)
     • Risks (scope mismatch, policy conflicts, timeline concerns)
     • Alternatives (backup journals)

Key Parameters / Notes

• NCBI

  EMAIL

  : required to comply with NCBI E-utilities usage policy.
• NCBI

  API_KEY

  : optional but recommended to reduce throttling and improve throughput.
• Output structuring: use

  assets/journal_recommendation_template.csv

  to ensure consistent fields and downstream usability.