EP01.08: Comparing clinical effectiveness of 2nd trimester cervical length for the detection of patients at risk of preterm birth in two referral centres
Bibliographic record
Abstract
The aim of this study is to compare clinical effectiveness of 2nd trimester cervical length measurements (CL) for the detection of patients at risk of preterm birth (PTB) in two different referral centres using Fryback-Thornbury model for clinical efficacy in diagnostic imaging (FTM). A retrospective study including patient's examined in January 2013 at tertiary referral medical centres in Canada and Israel. CL cutoff point ≤25 mm at 20–24 weeks. PTB ≤36 weeks. FTM analysis in four levels: Technical, Accuracy. Therapeutic and Outcome. See table 1. These preliminary results suggest a higher clinical effectiveness of CL in predicting PTB ≤36w in Centre A compared to Centre B, this trend will be better analysed in a larger study. FTM can be applied to compare the clinical effectiveness of CL for detecting pregnancies at risk for PTB between different centres.
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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".