The Effect of Computer-Assisted Evaluation of Labor on Cesarean Rates
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".