MétaCan
Menu
Back to cohort
Record W2930967286 · doi:10.1017/9781108421706

Eponyms and Names in Obstetrics and Gynaecology

2019· book· en· W2930967286 on OpenAlexaff
Thomas F. Baskett

Bibliographic record

VenueCambridge University Press eBooks · 2019
Typebook
Languageen
FieldArts and Humanities
TopicMedical History and Innovations
Canadian institutionsDalhousie University
Fundersnot available
KeywordsContext (archaeology)Obstetrics and gynaecologyHistory of medicineMedicineLibrary scienceHistoryClassicsPregnancyComputer science

Abstract

fetched live from OpenAlex

Few specialties have a longer or richer eponymous background than obstetrics and gynaecology. Eponyms add a human side to an increasingly technical profession and represent the historic tradition and language of the speciality. This collection aims to perpetuate the names and contributions of pioneers and offer introductory profiles to the founders in whose steps we follow. This third edition includes 26 new entries, as well as expanded detail, illustration and quotation for existing entries. Biographical data and historical and medical context are discussed for each of the 391 names, with reference to 34 countries, reflecting the field's far reaching origins. More than 1700 original references feature, alongside an extensive bibliography of more than 2500 linked references to assist readers searching for more detailed information. This is a volume for physicians, midwives, medical historians, medical ethicists and all those interested in the history and evolution of obstetrical and gynaecological treatment.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0030.007
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0200.009

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 head0.029
GPT teacher head0.183
Teacher spread0.155 · 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.

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

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

Citations6
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueCambridge University Press eBooksSame topicMedical History and InnovationsFrench-language works237,207