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Record W2512716213 · doi:10.1177/107327481602300307

Multidisciplinary Management of Salivary Gland Cancers

2016· review· en· W2512716213 on OpenAlex

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

VenueCancer Control · 2016
Typereview
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineMultidisciplinary approachSalivary glandSalivary gland cancerPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Salivary carcinomas are a rare group of biologically diverse neoplasms affecting the head and neck. The wide array of different histological entities and clinical presentations has historically limited attempts to establish well-defined treatment algorithms. In general, low-risk lesions can be managed with a single treatment modality, whereas advanced lesions require a more complex, multidisciplinary approach. METHODS: The relevant literature was reviewed, focusing on diagnostic and treatment algorithms for salivary malignancies. RESULTS: Salivary carcinomas with high-risk features require an aggressive treatment approach with complete surgical resection, neck dissection to appropriate cervical lymph-node basins, and postoperative radiotherapy. CONCLUSIONS: The heterogeneity of salivary neoplasms represents a unique clinical challenge. Despite the multidisciplinary management paradigm detailed in this review, outcomes for advanced disease are unsatisfactory. Future progress will likely require the addition of novel systemic therapeutic strategies.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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)0.0010.000

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 head0.372
Teacher spread0.331 · 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