Assimilating evidence quality at a glance using graphic display: research synthesis on labor induction
Bibliographic record
Abstract
Evidence profiled in the World Health Organization induction of labor guideline extended to 84 tables and 116 pages, which is hard to assimilate. Summarizing this evidence graphically can present information on key outcomes succinctly, illustrating where the gaps, strengths and weaknesses lie. For induction of labor, graphic representation clearly showed that evidence was lacking on maternal complications when comparing oxytocin with other agents, evidence was strong on birth within 24 h when comparing vaginal prostaglandins with placebo or no treatment, but again it was weak on uterine hyperstimulation when comparing oxytocin with vaginal prostaglandins. These graphs/plots allow readers to capture the essence of the information gathered at a glance. The use of graphical displays when interpreting and publishing data on several comparisons and outcomes is encouraged.
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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 | 0.175 | 0.633 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.040 | 0.036 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.045 | 0.006 |
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".