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The Effect of Computer-Assisted Evaluation of Labor on Cesarean Rates

2004· article· en· W2065212525 on OpenAlexaff
Emily Hamilton, Robert W. Platt, Robert Gauthier, Helen McNamara, Louise Miner, Susan Rothenberg, Guylaine Asselin, Robert Sabbah, Alice Benjamin, Marian Lake, Anthony M. Vintzileos

Bibliographic record

VenueJournal for Healthcare Quality · 2004
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsUniversité de MontréalMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineObstetricsCorrectnessCesarean deliveryPregnancy

Abstract

fetched live from OpenAlex

Dystocia, or slow labor, is the leading cause of first-time cesarean sections. Current diagnostic guidelines for dystocia are vague, and there is no clear postoperative confirmatory evidence to assess the correctness of this diagnosis. For several decades, various professional organizations have indicated that cesarean rates could be lowered safely and have recommended levels that are far below national averages. The three major factors, of roughly equal importance, associated with cesarean for slow labor are the baby's weight, the mother's height, and the threshold at which the physician believes it is reasonable to intervene. The last is the only modifiable factor, and quality programs are a major part of changing medical behavior. By using two study designs, the effect of a mathematical method for evaluating labor progress on the rate of cesarean section was measured. In the prospective randomized clinical trial, the relative risk of cesarean in the experimental group was unchanged at 1.04. In the pretest-posttest analysis, the rates fell from 19.54% to 17.04% at 6 months and 16.62% at 12 months.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score0.206

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
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)0.0000.000

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 head0.152
GPT teacher head0.527
Teacher spread0.375 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations16
Published2004
Admission routes1
Has abstractyes

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