Redefining classification of central neck dissection in differentiated thyroid cancer
Bibliographic record
Abstract
Therapeutic central neck dissection for differentiated thyroid cancer is recommended in the setting of clinically positive disease. The role of lymphadenectomy in patients with clinically negative disease is a matter of controversy and therefore extent of surgery varies. The boundaries of the central neck are variably described, as are the components of a central neck dissection. Patients with aggressive disease are managed with a comprehensive dissection, yet there is no classification system to distinguish this from a less rigorous operation. Therefore, there is variability in reporting and difficulty in the interpretation of results in the published literature. Here we propose a novel classification system for central neck dissection in thyroid cancer that allows accurate reporting of extent of surgery. The objectives are to reduce ambivalence and allow documentation of extent of lymphadenectomy, such that comparisons can be made between the varied strategies in the management of the central compartment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".