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Record W1982626132 · doi:10.1159/000079879

Outcomes Research in Head and Neck Cancer

2004· review· en· W1982626132 on OpenAlex
Kevin Fung, Jeffrey E. Terrell

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueORL · 2004
Typereview
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineQuality of life (healthcare)Head and neck cancerHead and neckCancerPhysical therapyDiseaseMedical physicsOncologyInternal medicineSurgery

Abstract

fetched live from OpenAlex

Quality of life (QOL) considerations are uniquely important in head and neck oncology outcomes research due to the multidimensional impact of these tumors and their treatment. Patient variables, tumor variables and treatment variables must be considered comprehensively in order to maximize the validity of QOL outcome measures. There are a multitude of QOL instruments, which can be classified into: (1) general measures of health-related QOL, (2) general QOL instruments for patients with cancer, (3) disease-specific instruments for patients with head and neck cancer, (4) treatment-specific instruments and (5) symptom-specific instruments. This article will highlight commonly used validated QOL instruments in head and neck oncology.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.288
GPT teacher head0.551
Teacher spread0.263 · 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