Development, translation, and preliminary validation of the neck dissection assessment tool
Bibliographic record
Abstract
BACKGROUND: The objective was to develop an assessment tool to evaluate residents' competency for neck dissection and provide preliminary evidence of feasibility, reliability, and validity. METHODS: Six surgeons developed a neck dissection assessment tool using a modified Delphi method and evaluated 58 neck dissections from six junior and six senior otolaryngology residents. RESULTS: The assessment tool uses a double checklist: a previously validated global rating scale (GRS) and a task-specific checklist (TSC). Use of the instrument appeared feasible and the average scores on the GRS and TSC differed significantly between junior and senior residents. The Pearson correlation coefficient between both checklists was 0.87. Intraclass correlation (ICC) for inter-rater reliability was 0.69 for the GRS, and 0.80 for the TSC. CONCLUSION: This study provides preliminary evidence of feasibility, reliability, and validity for the first neck dissection assessment tool and provides a foundation for further psychometric analysis and research.
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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 | 0.024 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".