search-big-labs-by-field

name	search_big_labs_by_field
description	Discover leading PI-led research groups in a scientific field using OpenAlex publication evidence, with ranking based mainly on overall scholarly impact, PI-like authorship patterns, and recent 10-year and 5-year activity summaries.

Search Big Labs by Field

Purpose

Use this skill when the user wants to identify important research labs, principal investigators, and institutions in a scientific field.

Typical use cases:

• find major labs in CRISPR, bioinformatics, or computational biology
• build a postdoc or collaboration target list
• understand the lab landscape of a field
• compare overall impact and recent activity of candidate PIs

This skill is publication-based and PI-oriented:

• it retrieves field-relevant papers
• aggregates authors from those papers
• filters for PI-like candidates
• profiles candidates with overall impact and recent publication summaries
• de-duplicates repetitive results

The final output is a ranked candidate lab list, where each row is a best-effort PI-centered lab proxy.

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When to use

Use this skill for questions like:

• “Find the big labs in CRISPR.”
• “Who are the top PIs in computational biology?”
• “Give me strong bioinformatics labs.”
• “Show leading groups in cancer genomics.”
• “Find important labs in single-cell computational biology.”
• “What are the main labs working on protein structure prediction?”

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When not to use

Do not use this skill when the user wants:

• a single official lab website
• exact lab size or membership
• a faculty directory lookup
• exact email scraping
• a paper summary or weekly paper report
• gene enrichment, annotation, or CRISPR design

This skill is for lab discovery, not for website lookup or administrative verification.

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Data source

This skill uses:

• OpenAlex works
• OpenAlex authors
• OpenAlex institutions

Current version:

• does not scrape lab websites
• does not search the web for official lab pages
• relies on structured publication and affiliation data only

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What the skill does

The workflow has seven main stages.

Step 1. Retrieve field-relevant papers

The script searches OpenAlex works using the user keyword and a configurable recent time window.

Goal:

• build a discovery corpus of papers relevant to the requested field

Step 2. Remove unsuitable papers

The script excludes:

• unsupported work types
• very large collaboration papers above a configurable authorship threshold

Goal:

• reduce noise from consortium papers and massive coauthor lists

Step 3. Aggregate authors

From the filtered papers, the script aggregates author-level evidence:

• relevant paper count
• citations across relevant papers
• authorship positions
• institutions seen
• matched keyword breadth
• candidate representative works

Goal:

• convert the paper set into a candidate PI pool

Step 4. Keep PI-like candidates

The script keeps only authors with sufficient PI-like authorship evidence, mainly:

• minimum last-author count
• or minimum first/last-author count

Goal:

• reduce inflation from middle authors and frequent collaborators

Step 5. Build PI profiles

For each surviving candidate, the script retrieves:

• overall citation count
• overall works count
• institution metadata
• recent 10-year and 5-year publication summaries
• representative papers

Goal:

• provide a richer profile for each candidate

Step 6. Rank by overall impact

Final ranking emphasizes:

• overall scholarly impact
• total work count
• field relevance
• PI-like authorship evidence

Recent publication counts are included for interpretation, but they are not the main ranking signal.

Goal:

• rank “important labs overall,” not merely the most recently prolific ones

Step 7. De-duplicate final results

The script reduces redundancy by:

• limiting rows per institution
• limiting excessive overlap of representative paper sets across rows

Goal:

• improve diversity and readability of the final candidate list

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Inputs

Required arguments

--keyword

The scientific field or topic to search.

Examples:

• CRISPR
• bioinformatics
• computational biology
• single-cell genomics
• cancer genomics
• protein structure prediction

--output

Path to the TSV output file.

Example:

• results/computational_biology_labs.tsv

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Optional arguments

--top-n

Number of final candidate labs / PIs to keep.

Default:

• 30

Use a larger value when the user wants a broader landscape. Use a smaller value when the user wants a short, high-confidence shortlist.

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--max-works

Maximum number of keyword-relevant works retrieved from OpenAlex during the initial discovery stage.

Default:

• 300

Higher values:

• improve recall
• increase runtime
• may increase noise for broad keywords

Lower values:

• run faster
• may miss some important candidates

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--per-page

Pagination size for OpenAlex works retrieval.

Default:

• 100

Usually this can be left unchanged.

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--years-back

How many recent years of works are used for the initial discovery stage.

Default:

• 5

Meaning:

• the initial paper pool is built from this recent window

Use smaller values if:

• the user wants the current landscape only

Use larger values if:

• the field has important older foundational papers
• famous PIs may otherwise be missed

For example:

• 5 is often good for broad current fields
• 10 is often better for CRISPR and other iconic mature fields

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--author-works-limit

Maximum number of recent works retrieved per candidate PI during the profiling stage.

Default:

• 150

This affects:

• recent paper summaries
• representative papers
• recent activity fields

Higher values:

• provide richer profiles
• increase runtime

Lower values:

• run faster
• may reduce profile completeness

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--sleep-seconds

Pause between detail requests to reduce API pressure.

Default:

• 0.2

Increase if:

• API requests appear throttled

Decrease slightly if:

• speed matters and the API remains stable

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--max-authors-per-paper

Exclude papers with more than this many authorships.

Default:

• 20

This is one of the most important quality-control parameters.

Purpose:

• remove very large collaboration papers
• reduce repeated institutions and paper clusters
• reduce coauthor inflation

Use stricter values for:

• broad fields like computational biology or bioinformatics

Use looser values for:

• collaboration-heavy fields like CRISPR

Examples:

• 20 for broad/noisy fields
• 60 for CRISPR-like fields

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--min-last-author-count

Minimum last-author count for PI-like filtering.

Default:

• 2

Purpose:

• favor likely lab leaders rather than collaborators

Higher values:

• stricter PI filtering
• more precision
• risk missing some important PIs

Lower values:

• better recall
• more noise

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--min-first-last-author-count

Minimum combined first/last-author count for PI-like filtering.

Default:

• 3

Purpose:

• rescue candidates who may not have many last-author papers but still show strong leadership-style authorship

This works together with --min-last-author-count.

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--max-per-institution

Maximum number of final rows retained per institution.

Default:

• 2

Purpose:

• prevent one institution from dominating the final list

Lower values:

• more institution diversity

Higher values:

• more depth within dominant institutions

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--max-paper-overlap

Maximum allowed DOI overlap between selected rows.

Default:

• 2

Purpose:

• avoid highly repetitive candidate rows
• reduce cases where multiple coauthors from one paper cluster all appear in the final list

Lower values:

• stronger diversification

Higher values:

• more tolerance for similar paper sets

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--output-jsonl

Optional JSONL output path.

Use this when a machine-readable row-by-row format is also needed.

Example:

• results/computational_biology_labs.jsonl

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Parameter decision guide

Signal in user request	Parameter to set
"top 10 labs" / concise shortlist	--top-n 10
"broad landscape" / "many labs"	--top-n 50
"only recent active labs"	--years-back 3
"mature / established field" (e.g. CRISPR, genomics)	--years-back 10 (catch founders who publish less now)
"broad noisy keyword" (e.g. "bioinformatics")	--max-authors-per-paper 15 (stricter, less noise)
"collaboration-heavy field" (e.g. "CRISPR")	--max-authors-per-paper 60 (looser)
"more diversity across institutions"	--max-per-institution 1
"depth within top institutions"	--max-per-institution 3
"stricter PI filter" (senior PIs only)	--min-last-author-count 5
"broader PI filter" (include rising PIs)	--min-last-author-count 1 --min-first-last-author-count 2
"faster / fewer results needed"	--max-works 100
"comprehensive / more recall"	--max-works 500
Also need machine-readable output	add --output-jsonl results/labs.jsonl

Outputs

Main output

A TSV file with one row per candidate lab / PI.

Optional output

A JSONL file with one record per row.

Typical columns

Identity and affiliation

• query_keyword
• lab_name
• pi_name
• institution_name
• institution_type
• city
• country_code
• institution_homepage
• orcid
• openalex_author_id
• institution_openalex_id
• institution_ror

Ranking and evidence

• relevance_score
• overall_cited_by_count
• overall_works_count
• query_relevant_works_count
• query_total_citations_from_relevant_works
• first_last_author_count
• last_author_count
• first_author_count
• matched_keyword_terms

Topic summary

• lab_type
• main_methods
• main_topics
• top_topics
• topic_share
• research_summary

Recent activity

• publications_last_10y
• publications_last_5y
• publications_last_3y
• keyword_relevant_papers_last_10y
• keyword_relevant_papers_last_5y
• keyword_relevant_papers_last_3y
• publication_year_distribution_last_10y

Representative papers

• representative_papers_overall_10y
• representative_keyword_relevant_papers
• recent_papers_last_5y

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How to interpret the output

lab_name

Usually a convenience label like:

• <PI name> Lab

It is not guaranteed to be the official lab title.

relevance_score

A heuristic ranking score combining:

• field relevance
• overall impact
• PI-like authorship evidence

Useful for:

• sorting
• comparison
• shortlist construction

Not intended as:

• a universal bibliometric metric

overall_cited_by_count

Overall OpenAlex citations for the candidate PI.

overall_works_count

Overall OpenAlex works for the candidate PI.

publications_last_10y and publications_last_5y

Recent activity summaries. These are included for context, not as the dominant ranking driver.

representative_papers_overall_10y

Top overall representative papers from the last 10 years.

representative_keyword_relevant_papers

Top representative papers specifically relevant to the queried field.

recent_papers_last_5y

Representative recent papers to help judge current activity.

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Execution

Entry point

python scripts/search_big_labs_by_field.py --keyword "<field>" --output <output_tsv>