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Record W4238500546 · doi:10.1002/9780471420194.tnmm43

Oropharynx

2017· other· en· W4238500546 on OpenAlexaff
Shao Hui Huang, Hisham Mehanna, Jan B. Vermorken, Brian O’Sullivan

Bibliographic record

VenueTNM Online · 2017
Typeother
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineInternal medicineEtiologyHuman papillomavirusOncologyBasal cellClinical trialDiseaseDermatologyPathology

Abstract

fetched live from OpenAlex

Summary More than 90% oropharyngeal cancers (OPC) are squamous cell carcinoma (SCC). Based on the aetiology, SCC of the oropharynx can be classified into two major distinct disease entities: smoking/alcohol‐related (HPV‐negative) and human papillomavirus‐related (HPV‐positive) OPC. The two diseases have different molecular signatures, histopathological features, clinical behaviours and outcomes. Although treatment does not differ at present, emerging evidence suggests that a subset of HPV‐positive OPC patients should be considered for treatment de‐intensification trials. Several clinical trials are in‐design or on‐going to address separate treatment options for the different risk groups of HPV‐positive and ‐negative OPC.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.028
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0170.001

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.

Opus teacher head0.042
GPT teacher head0.369
Teacher spread0.327 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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