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Geographic delivery models for radiotherapy services

2002· article· en· W2143348144 on OpenAlexaff
Gisele Roberts, Peter Dunscombe, Rajiv Samant

Bibliographic record

VenueAustralasian Radiology · 2002
Typearticle
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsLaurentian UniversityUniversity of OttawaNortheast Cancer Centre
Fundersnot available
KeywordsMedicineRadiation therapyMedical physicsRadiology

Abstract

fetched live from OpenAlex

The study described here was undertaken to quantify the societal cost of radiotherapy in idealized urban and rural populations and, hence, to generate a measure of impediment to access. The costs of centralized, distributed comprehensive and satellite radiotherapy delivery formats were examined by decomposing them into institutional, productivity and geographical components. Our results indicate that centralized radiotherapy imposes the greatest financial burden on the patient population in both urban and rural scenarios. The financial burden faced by patients who must travel for radiotherapy can be interpreted as one component of the overall impediment to access. With advances in remote-monitoring systems, it is possible to maintain technical quality while enhancing patient access. However, the maintenance of professional competence will remain a challenge with a distributed service-delivery format.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

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

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 head0.022
GPT teacher head0.318
Teacher spread0.296 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations18
Published2002
Admission routes1
Has abstractyes

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