Impact of nodal ratio on survival in squamous cell carcinoma of the oral cavity
Bibliographic record
Abstract
BACKGROUND: The association between nodal ratio and survival has not been assessed in squamous cell carcinomas of the head and neck. METHODS: This is a population-based analysis, using the Surveillance, Epidemiology, and End-Results database, to determine whether nodal ratio impacts survival in patients with oral cavity squamous cell carcinoma. RESULTS: Between 1988 and 2005, 2955 new diagnoses of N(1) or N(2) squamous cell carcinoma of the oral cavity were identified. The mean nodal ratio was 16.9%. Nodal ratio was found to be strongly statistically associated with overall survival in both univariate and multivariate analyses. Patients could be stratified into low- (0% to 6%), moderate- (6% to 12.5%), and high-risk (>12.5%) groups based on nodal ratio. CONCLUSIONS: In patients with squamous cell carcinoma of the oral cavity, an increased nodal ratio is a strong predictor of decreased survival. Risk of death can be stratified based on nodal ratio.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".