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Record W4213416131 · doi:10.1057/s41599-022-01085-9

Correction: Sex and gender considerations in health research: a trainee and allied research personnel perspective

2022· article· en· W4213416131 on OpenAlexafffund
Cindy Z. Kalenga, Jeanna Parsons Leigh, Janessa Griffith, Daniele C. Wolf, Sandra M. Dumanski, Arlene Desjarlais, Lisa Petermann, Sofia B. Ahmed

Bibliographic record

VenueHumanities and Social Sciences Communications · 2022
Typearticle
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsUniversité de MontréalWomen's College HospitalAlberta Kidney Disease NetworkUniversity of TorontoDalhousie UniversityLibin Cardiovascular Institute of Alberta
FundersInstitute of Gender and HealthCanadian Institutes of Health Research
KeywordsPerspective (graphical)PsychologyEngineering ethicsMedical educationApplied psychologyMedicineEngineeringComputer science

Abstract

fetched live from OpenAlex

Correction to: Humanities and Social Sciences Communications https://doi.org/10.1057/s41599-020-00643-3 , published online 16 November 2020.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.268
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.268
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0040.005
Science and technology studies0.0090.010
Scholarly communication0.0090.006
Open science0.0080.005
Research integrity0.0210.034
Insufficient payload (model declined to judge)0.0540.036

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.833
GPT teacher head0.552
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainMethods
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes2
Has abstractyes

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