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Record W1991448432 · doi:10.1586/era.10.9

Magnetic resonance imaging of nasopharyngeal carcinoma

2010· review· en· W1991448432 on OpenAlex
Eugene Yu, Brian O’Sullivan, John Kim, Lillian L. Siu, Eric Bartlett

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

VenueExpert Review of Anticancer Therapy · 2010
Typereview
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsNasopharyngeal carcinomaMedicineMagnetic resonance imagingRadiation therapyRadiologyNasopharyngeal cancerModality (human–computer interaction)Oncology

Abstract

fetched live from OpenAlex

Nasopharyngeal carcinoma (NPC) is a malignant tumor that its the highest rates in Southeast Asia. It is a locally aggressive neoplasm that has a propensity for developing regional neck adenopathy. The main treatment modality consists primarily of radiation therapy. Cross-sectional imaging is important in order to achieve an accurate delineation of tumor extent, thereby facilitating both staging and treatment. MRI is currently considered the best modality to assess for NPC. The aim of this review is to provide a pictorial MRI review of NPC according to the recently released 7th edition of the International Union Against Cancer 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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.001
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)0.0010.000

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 head0.041
GPT teacher head0.387
Teacher spread0.346 · 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