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Squamous Cell Carcinoma of the Head and Neck in Ontario, Canada, and in Southeastern Norway

2003· article· en· W1979202605 on OpenAlexaffabout
Stephen F. Hall, Morten Boysen, Patti A. Groome, William J. Mackillop

Bibliographic record

VenueThe Laryngoscope · 2003
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsQueen's University
FundersWorld Health Organization
KeywordsMedicineHead and neckBasal cellHead and neck cancerHead and neck squamous-cell carcinomaProspective cohort studyInternal medicineSignificant differenceOverall survivalStatistical analysisOncologyRetrospective cohort studyCancerDemographySurgeryStatistics

Abstract

fetched live from OpenAlex

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 regional cancer centers in southeastern Ontario, Canada, and southeastern Norway were compared. STUDY DESIGN: Retrospective comparative study of two prospective databases. METHODS: The case mix, treatments, and disease-specific mortality were compared using frequency tables, Kaplan-Meier survival curves, and the log rank test. RESULTSThe case mix, except for differences in oral cavity, oropharynx, and the recorded tumor (T) category, was similar, and the treatments were different. There was no statistical difference 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 survival suggest a difference in staging assignment and raises a question about the reliability of the TNM staging process.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.214

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.224
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2003
Admission routes2
Has abstractyes

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