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Record W2807413965 · doi:10.2217/ebo.13.739

Nasopharyngeal cancer staging

2014· other· en· W2807413965 on OpenAlexaff
John Kim

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineNasopharyngeal carcinomaCancerRadiation oncologistRadiation therapyHead and neck cancerCancer stagingNasopharyngeal cancerOncologyInternal medicineRadiation oncologyMedical physics

Abstract

fetched live from OpenAlex

Summary The staging of cancer is done in accordance with a set of principles, guidelines, rules and nomenclature of standardized staging systems. Two universally accepted systems are the International Union against Cancer (UICC) TNM Classification of Malignant Tumors and the American Joint Committee on Cancer (AJCC) Cancer Staging Manual. For the purposes of staging nasopharyngeal cancer, these systems are identical. This chapter will review the principles of staging nasopharyngeal cancer using the UICC/AJCC staging system and highlight the importance of staging in clinical practice. This chapter will also review the changes from the sixth to seventh edition of the UICC/AJCC staging system.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.061
Threshold uncertainty score0.204

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0610.018

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 head0.022
GPT teacher head0.325
Teacher spread0.303 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2014
Admission routes1
Has abstractyes

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