MétaCan
Menu
Back to cohort
Record W4389686299 · doi:10.1001/jamasurg.2023.6397

Fertility, Family, and a Career in Surgery—Time to Change the Narrative

2023· letter· en· W4389686299 on OpenAlexaff
J. Elaine Tang, Melina C. Vassiliou, Liane S. Feldman

Bibliographic record

VenueJAMA Surgery · 2023
Typeletter
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineFertilityNarrativeMedical schoolResidency trainingMedical educationFamily medicinePopulation

Abstract

fetched live from OpenAlex

Medical training usually falls within the window of optimal fertility for most trainees.1 Operating within the rigid confines of residency programs, the perceived realities of family planning can strongly bias medical students when making career choices about specialties.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.068
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.125
GPT teacher head0.290
Teacher spread0.166 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJAMA SurgerySame topicDiversity and Career in MedicineFrench-language works237,207