Becoming a congenital heart surgeon: the long and challenging road
Bibliographic record
Abstract
Training in congenital cardiac surgery is potentially lengthier and more demanding than training in any other surgical field. The duration of training is proportional to the complexity of the specialization. The expertise of a wide range of procedures is required. There is no doubt that some individuals may acquire the requisite abilities with greater ease than others, but fundamentally, these are capabilities that can be taught and learnt. Moreover, congenital cardiac surgeons are required to have a detailed understanding of pathophysiology and morphology, in addition to the stamina and empathy required to manage these complex patients. A fellowship is just the start of such training and is followed by a long road eventually leading to a lifelong journey to become a qualified congenital cardiac surgeon. Effective mentorship is a prerequisite throughout training to guide surgeons on this journey.
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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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.008 | 0.020 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".