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Record W2187939544

Cancer-related oral health care services and resources: a survey of oral and dental care in Canadian cancer centres.

2004· article· en· W2187939544 on OpenAlexaboutno aff
Joel B. Epstein, Ira R. Parker, Matthew S. Epstein, Peter Stevenson‐Moore

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldMedicine
TopicOral health in cancer treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCancerDental careFamily medicineOral healthQuality of life (healthcare)NursingInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

PURPOSE: Prevention and management of oral complications of cancer and cancer therapy will improve oral function and quality of life, and reduce morbidity and the cost of care. Oral assessment, and oral and dental care have been strongly recommended before cancer therapy and should be continued during and after cancer therapy. The purpose of this survey was to assess the resources available for oral care in Canadian cancer centres. METHODS: Provincial cancer centres were assessed by questionnaire to determine the resources available for oral care in these facilities. RESULTS: Wide variability in oral and dental care of patients with cancer across Canada and a lack of documented standards of care were reported. Very few cancer centres had institutionally supported dental staff to support the oral care of patients with cancer, and few had dental treatment capability on site. The majority of centres managed oral care needs in the community with the patient's prior dentist. CONCLUSIONS: We recommend that national guidelines be developed for medically necessary oral and dental care for patients with cancer.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.033
GPT teacher head0.323
Teacher spread0.290 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations32
Published2004
Admission routes1
Has abstractyes

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