The pediatric hematology/oncology educational laboratory in‐training examination (PHOELIX): A formative evaluation of laboratory skills for Canadian pediatric hematology/oncology trainees
Bibliographic record
Abstract
BACKGROUND: Pediatric hematologists/oncologists need to be skilled clinicians, and must also be adept and knowledgeable in relevant areas of laboratory medicine. Canadian training programs in this subspecialty have a minimum requirement for 6 months of training in acquiring "relevant laboratory diagnostic skills." The Canadian pediatric hematology/oncology (PHO) national specialty society, C17, recognized the need for an assessment method in laboratory skills for fellows graduating from PHO training programs. PROCEDURE: Canadian pediatric hematologists/oncologists were surveyed regarding what were felt to be the essential laboratory-related knowledge and skills deemed necessary for graduating pediatric hematology/oncology trainees. The PHOELIX (Pediatric hematology/oncology educational laboratory in-training examination) was then developed to provide an annual formative evaluation of laboratory skills in Canadian PHO trainees. RESULTS: The majority of PHO respondents (89%) felt that laboratory skills are important in clinical practice. An annual formative examination including review of glass slides was implemented starting in 2010; this provides feedback regarding knowledge of laboratory medicine to both trainees and program directors (PDs). CONCLUSIONS: We have successfully created a formative examination that can be used to evaluate and educate trainees, as well as provide PDs with a tool to gauge the effectiveness of their laboratory training curriculum. Feedback has been positive from both trainees and PDs.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".