Introduction of new techniques and technologies in surgery: Where is transanal total mesorectal excision today?
Bibliographic record
Abstract
The introduction of new surgical techniques and technologies has traditionally been unregulated. In many settings surgeons frequently adopt novel procedures without following a structured program of implementation or supervision. The appearance of innovative technology played a pivotal role in the advancement of new surgical techniques during the industrial revolution. Innovation has been an essential component of surgical development, which led to contemporary surgical techniques such as minimally invasive surgery. Different initiatives have been developed to guide the safe introduction of new surgical techniques and other procedures. Those include comprehensive concepts such as the Idea, Development, Exploration, Assessment, Long-term study framework, which could be particularly relevant when reflecting on the novel transanal total mesorectal excision (taTME), introduced a decade ago. This relatively novel and complex procedure promised to overcome some of the major limitations of traditional surgical approaches for rectal cancer. According to the Idea, Development, Exploration, Assessment, Long-term study framework, taTME is in the phase of exploration, where there is an existing and increasing number of reports being published as the experience grows. The current management of rectal cancer is in a state of radical evolution, with multiple options that were not previously available. TaTME is only one technique amongst many which could be part of a rectal cancer surgeon's armamentarium; however, it requires further rigorous study and evaluation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".