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Record W2767138633 · doi:10.1093/jjco/hyx148

Radiation oncology in Canada

2017· review· en· W2767138633 on OpenAlexafffundabout
Meredith Giuliani, Mary Gospodarowicz

Bibliographic record

VenueJapanese Journal of Clinical Oncology · 2017
Typereview
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
FundersCanadian Association of Radiation Oncology
KeywordsMedicineRadiation oncologyRadiation therapyReferralRadiation TherapistHealth careClinical PracticeMedical physicsHealthcare systemFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

In this article we provide an overview of the Canadian healthcare system and the cancer care system in Canada as it pertains to the governance, funding and delivery of radiotherapy programmes. We also review the training and practice for radiation oncologists, medical physicists and radiation therapists in Canada. We describe the clinical practice of radiation medicine from patients' referral, assessment, case conferences and the radiotherapy process. Finally, we provide an overview of the practice culture for Radiation Oncology in Canada.

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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.460

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.002

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 head0.244
GPT teacher head0.615
Teacher spread0.370 · 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
GenreReview

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

Citations5
Published2017
Admission routes3
Has abstractyes

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Same venueJapanese Journal of Clinical OncologySame topicAdvances in Oncology and RadiotherapyFrench-language works237,207