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Record W2001747990 · doi:10.1586/era.12.9

Perineural invasion and spread in head and neck cancer

2012· review· en· W2001747990 on OpenAlex
Meredith Johnston, Eugene Yu, John Kim

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 · 2012
Typereview
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicinePerineural invasionRadiation therapyHead and neckHead and neck cancerSalivary gland cancerCancerDiseaseOncologyPathologyInternal medicineRadiologySurgery

Abstract

fetched live from OpenAlex

Perineural involvement is a well-recognized clinicopathologic entity found in head and neck (H&N) cancers, including mucosal epithelial carcinomas and salivary gland malignancies. Perineural disease remains a diagnostic, prognostic and therapeutic challenge for the multidisciplinary H&N oncology team. Nerves are important routes of tumor spread in H&N malignancies, yet the biology and prognostic implications of perineural tumor growth are not fully understood. On balance, the available evidence suggests that it is associated with an increased risk of locoregional recurrence but the impact on survival remains uncertain. Perineural involvement has implications for locoregional disease diagnosis and management. MRI is the best imaging modality to detect tumor extent. Advanced radiotherapy technologies such as intensity-modulated radiation therapy and image-guided radiation therapy have the potential for more accurate targeting and treatment of anatomically complex patterns of disease spread. This review is limited to nondermatologic H&N cancers.

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 score0.932
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
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 head0.100
GPT teacher head0.429
Teacher spread0.329 · 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