Education of the clinical embryology laboratory professional: development of a novel program delivered in a laboratory medicine department
Bibliographic record
Abstract
Clinical embryologists are responsible for the handling, evaluation, and care of human gametes and preimplantation embryos within the context of an assisted reproductive technology laboratory. They are integral members of a team of professionals who provide care for fertility patients. Despite the increasing recognition of clinical embryologists as professionals, training requirements, continuing professional development, and appropriate credentialing have lagged in several countries. In many cases, individuals enter the profession with training limited to technical aspects provided by individual laboratory directors through an apprenticeship model. In this article, we present the rationale for rigorous formal training in clinical embryology, introduce CanEMB competencies for practicing professional clinical embryologists that are founded on CanMEDs role principles, and present a nascent Masters of Health Sciences degree program in Laboratory Medicine with a specialization in clinical embryology. This 2-year program has unique features including a Clinical Embryology Skills Development Laboratory, research capstone project, and 200-hour placement within a practicing assisted reproductive technology laboratory. Importantly, this program is delivered through a university-based Department of Laboratory Medicine and Pathobiology in partnership with a Department of Obstetrics and Gynecology. Thus, this program represents a formal acceptance of clinical embryology as a clinical laboratory science. It can be adopted elsewhere to provide a relevant, robust education that will meet current and future needs of the profession.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".