A Biased Coin Up-and-Down Sequential Allocation Trial to Determine the Optimum Programmed Intermittent Epidural Bolus Time Interval Between 5 mL Boluses of Bupivacaine 0.125% With Fentanyl 2 µg/mL
Bibliographic record
Abstract
(Can J Anesth. 2019 66:1075–1081) Programmed intermittent epidural bolus (PIEB) for labor analgesia has garnered a lot of attention and is the focus of ongoing research. PIEB when compared with continuous epidural infusion results in higher maternal satisfaction, reduced local anesthetic consumption, lower incidence of motor block, fewer unilateral blocks, and less breakthrough pain. The optimal epidural solution and PIEB settings for labor analgesia have yet to be decided. This study aimed to determine the effective PIEB time interval when using 5 mL boluses of bupivacaine 0.125% with fentanyl 2 mcg/mL.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".