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Record W1932980672 · doi:10.1177/014107680009300703

Urgency of caesarean section: A new classification

2000· article· en· W1932980672 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Royal Society of Medicine · 2000
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsSection (typography)Caesarean sectionComputer scienceMedicineData sciencePregnancyInformation retrievalWorld Wide WebGynecologyBiologyOperating system

Abstract

fetched live from OpenAlex

A new classification for caesarean section was developed in a two-part study conducted at six hospitals. Initially, 90 anaesthetists and obstetricians graded ten clinical scenarios according to five different classification methods--visual analogue scale; suitable anaesthetic technique; maximum time to delivery; clinical definitions; and a 1-5 rating scale. Clinical definitions was the most consistent and useful, and this method was then applied prospectively to 407 caesarean sections at the same six hospitals. There was close agreement (86%) between anaesthetists and obstetricians for the five-point scale (weighted kappa 0.89), increasing to 90% if two categories were combined (weighted kappa 0.91). We suggest that the resultant four-grade classification system--(i) immediate threat to life of woman or fetus; (ii) maternal or fetal compromise which is not immediately life-threatening; (iii) needing early delivery but no maternal or fetal compromise; (iv) at a time to suit the patient and maternity team--should be adopted by multidisciplinary groups with an interest in maternity data collection.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.044
GPT teacher head0.335
Teacher spread0.291 · 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