Comprehensive Evaluation of Hemostasis in Normal Women
Bibliographic record
Abstract
Women with mild bleeding disorders (MBDs) pose a diagnostic challenge and menorrhagia, the most common presenting symptom that remains underreported. We tested the hypothesis that screening apparently normal females using general and gynecological bleeding assessment tools and a global hemostatic assay together with platelet aggregation can help predict MBDs. We assessed 47 women using electronic bleeding assessment tools; e-bleeding questionnaire; and e-Pictorial Bleeding Assessment Chart (e-PBAC) based on previously validated methods, thrombelastography (TEG), and platelet aggregation together with basic coagulation testing. Three women had elevated bleeding score with von Willebrand disease diagnosis confirmed in one case and eleven cases had elevated e-PBAC. We report normal ranges for TEG and platelet aggregation in women during the first half of the menstrual cycle and show 23.4% of apparently normal women may have general or heavy menstrual bleeding. This is a prelude to a larger study to determine the validity of bleeding assessment tools in screening for MBDs in women.
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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 | 0.001 | 0.000 |
| 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".