Squamous Cell Carcinoma of the Head and
Bibliographic record
Abstract
Objectives/Hypothesis: Reports comparing case mix, treatments, and outcomes between different countries are uncommon in head and neck oncology. Prospective databases of unselected patients from re-gional cancer centers in southeastern Ontario, Can-ada, and southeastern Norway were compared. Study Design: Retrospective comparative study of two pro-spective databases. Methods: The case mix, treat-ments, and disease-specific mortality were compared using frequency tables, Kaplan-Meier survival curves, and the log rank test. Results: The case mix, except for differences in oral cavity, oropharynx, and the re-corded tumor (T) category, was similar, and the treat-ments were different. There was no statistical differ-ence in overall survival for all patients, as well as for some sites. Conclusions: The results of treatments, based on different overall treatment polices, for all patients were similar. The differences in recorded T category with no statistical difference in overall sur-vival suggest a difference in staging assignment and raises a question about the reliability of the TNM staging process. Key Words: Squamous carcinoma, head and neck, treatment, outcome analysis, reliabil-
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".