Fetal-Maternal Hemorrhage Detection in Ontario
Bibliographic record
Abstract
The results from fetal-maternal hemorrhage (FMH) detection and quantitation external quality assessment surveys conducted in Ontario indicate that the rosette test had a sensitivity and specificity for an FMH of more than 10 mL of 1.0 and 0.75, respectively, compared with 0.96 and 0.92, respectively, for acid elution. With FMH quantitation, the percentage error of the mean from the target FMH was 20% or more in 7 of 8 surveys, and coefficients of variation ranged from 39.5% to 71.8%. Inadequate Rho(D) immune globulin prophylaxis could have occurred in 19.4% of the challenges with an FMH of more than 10 mL. The rosette and acid elution techniques are both effective for the detection or exclusion of FMH, but acid elution lacks adequate accuracy and precision for reliable FMH quantitation. Furthermore, a strategy of prescribing an extra 1,500-IU Rho(D) immune globulin dose, in addition to the dose required to treat the volume of fetal blood detected, is an effective strategy to overcome the limitations of FMH quantitation by acid elution.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".