Canadian taTME expert collaboration (CaTaCO) position statement
Bibliographic record
Abstract
INTRODUCTION: Transanal total mesorectal excision (taTME) is a novel approach to surgery for rectal cancer. The technique has gained significant popularity in the surgical community due to the promising ability to overcome technical difficulties related to the access of the distal pelvis. Recently, Norwegian surgeons issued a local moratorium related to potential issues with the safety of the procedure. Early adopters of taTME in Canada have recognized the need to create guidelines for its adoption and supervision. The objective of the statement is to provide expert opinion based on the best available evidence and authors' experience. METHODS: The procedure has been performed in Canada since 2014 at different institutions. In 2016, the first Canadian taTME congress was held in the city of Toronto, organized by two of the authors. In early 2019, a multicentric collaborative was established [The Canadian taTME expert Collaboration] which aimed at ensuring safe performance and adoption of taTME in Canada. Recently surgeons from 8 major Canadian rectal cancer centers met in the city of Toronto on December 7 of 2019, to discuss and develop a position statement. There in person, meeting was followed by 4 rounds of Delphi methodology. RESULTS: The generated document focused on the need to ensure a unified approach among rectal cancer surgeons across the country considering its technical complexity and potential morbidity. The position statement addressed four domains: surgical setting, surgeons' requirements, patient selection, and quality assurance. CONCLUSIONS: Authors agree transanal total mesorectal excision is technically demanding and has a significant risk for morbidity. As of now, there is uncertainty for some of the outcomes. We consider it is possible to safely adopt this operation and obtain adequate results, however for this purpose it is necessary to meet specific requirements in different domains.
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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 | 0.015 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.011 | 0.006 |
| Insufficient payload (model declined to judge) | 0.061 | 0.017 |
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".