Implausible Birth Weight for Gestational Age
Bibliographic record
Abstract
Various rules have been proposed to identify and exclude live births with implausible values of birth weight for gestational age from large perinatal data sets. The authors carried out a preliminary evaluation of common rules by examining the frequency and nature of rule-based exclusions among live births in Canada (excluding Ontario) between 1992 and 1994. There were 625 (0.09%), 133 (0.02%), 170 (0.02%), and 2,858 (0.40%) live births identified for exclusion by a median birth weight for gestational age +/-4 standard deviations (SD) rule, a +/-5 SD rule, a rule based on expert clinical opinion, and a modification of Tukey's rule, respectively. The birth weight and gestational age distribution of the exclusions depended on the particular rule used; for example, 12.1% and 0.3% of live births of > or =4,500 g were excluded under Tukey's rule and the rule based on expert opinion, respectively. Infant mortality rates among those excluded were 8-13 times higher than among all live births. Current rules for identifying implausible birth weight for gestational age tend to flag live births at high risk for infant death. Such rules may erroneously attenuate temporal trends in important perinatal outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".