A pilot study to assess physician knowledge in transfusion medicine
Bibliographic record
Abstract
INTRODUCTION: An assessment of transfusion medicine knowledge and practice in Canada was carried out over a 3-week period. METHODS: Fifty-five questions were posed to evaluate both basic information on blood and blood products and on clinical use. The form was distributed through the Canadian Society for Transfusion Medicine with designated individuals asked to handle regional distribution. Some used provincial mailing lists, others distributed within each hospital. Approximately, 2000 forms were sent, including 500 in French. RESULTS: A total of 294 forms were returned; answers were recorded as 'correct', 'incorrect', 'no answer' or with 'added comments'. Overall, 52% of the questions were answered correctly or were answered with qualifying comments. In clinical practice questions, 63% were answered correctly or with qualifying comments. Basic knowledge questions drew correct answers in 37% of the cases. Several issues were answered poorly. The volume of an apheresis plasma unit was correctly estimated by less than 10% of respondents with many understanding the volume (500-600 mL) by as much as 300-400 mL. Anaesthesiologists responded most often (21%); few haematologists participated (4%). Provincial response varied: most were received from Ontario (30%) and British Columbia (22%). CONCLUSIONS: The answers show that clinical application of transfusion is generally accompanied by a questioning process - it is not entirely by rote. Basic knowledge about products needs improvement.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".