Teaching impact in pediatric minimal access surgery: Personal perspective from "Fellow"
Bibliographic record
Abstract
The global objective of this paper is to review from the "Fellow" perspective, the current status of pediatric minimal access surgery (MAS) in terms of teaching feasibility, safety and impact on standard practice paradigms. In the pediatric general surgery field, surgeons are dealing with a wide range of pathology that includes thoracic, abdominal, urological and gynecological procedures. The learning curve is slow because of a relatively small volume of patients. However, gradually but steadily, a significant proportion of the procedures traditionally performed, with major open exposures at present, are preferentially performed by minimal access. Currently, minimal access surgery training is incorporated into adult general surgery residency/fellowship programs and teaching techniques of pediatric MAS are available only as seldom international workshops. Pediatric surgery fellowship programs with incorporated guidelines for MAS training are just recently feasible in select centers, mostly as "self" established programs. In many other pediatric surgery centers, teaching the "glamour" of MAS is quite dependent on a program director's vision. Integration of MAS training into the secondary residency/fellowship curriculum of pediatric surgeons is the inevitable goal. MAS- minded education and research through adequate training will pay dividends and "manufacture" competent, contemporary trainees. National Pediatric Surgery Associations should be responsible for setting criteria that consider the MAS for accreditation with maintaining the international standards of these teaching programs.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".