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Record W2162077153 · doi:10.2217/fon.15.153

Rapid Access Palliative Radiation Therapy Programs: An Efficient Model of Care

2015· review· en· W2162077153 on OpenAlexaff
Kristopher Dennis, Kelly Linden, Tracy A. Balboni, Edward Chow

Bibliographic record

VenueFuture Oncology · 2015
Typereview
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsUniversity of TorontoSunnybrook Health Science CentreOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineMultidisciplinary approachPalliative careNarrative reviewRadiation therapyRadiation oncologyMedical physicsIntensive care medicineNursingInternal medicine

Abstract

fetched live from OpenAlex

Palliating symptoms of advanced and metastatic cancers are one of the most common indications for radiation therapy (RT), and the demand for palliative RT is increasing. Dedicated rapid access palliative RT programs improve access to care, and can deliver RT in a more efficient and evidence-based manner than standard RT programs. In this narrative review, we discuss the role of palliative RT in comprehensive cancer care, and challenges that have faced patients trying to access it. We describe how rapid access programs developed to address these challenges and provide an overview of dedicated programs worldwide. Finally, we show how these programs can serve as models for multidisciplinary care and education, and sources of exciting research opportunities in clinical care and advanced technologies.

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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.177
GPT teacher head0.461
Teacher spread0.284 · 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

Citations29
Published2015
Admission routes1
Has abstractyes

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