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Record W7071198960

Radiotherapy: Seizing the opportunity in cancer care

2019· report· en· W7071198960 on OpenAlexaboutno aff

Bibliographic record

VenueTrinity's Access to Research Output (TARA) (Trinity College Dublin) · 2019
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCancerRadiation therapyQuarter (Canadian coin)Cancer incidenceHealth careCancer treatmentIncidence (geometry)
DOInot available

Abstract

fetched live from OpenAlex

The incidence of cancer is increasing, resulting in a rising demand
\nfor high?quality cancer care. In 2018, there were close to 4.23 million
\nnew cases of cancer in Europe, and this number is predicted to rise
\nby almost a quarter to 5.2 million by 2040.1 This growing demand poses
\na major challenge to healthcare systems and highlights the need to ensure
\nall cancer patients have access to high-quality, efficient cancer care.
\nOne critical component of cancer care is too often forgotten in these
\ndiscussions: radiotherapy. Radiotherapy is recommended as part of
\ntreatment for more than 50% of cancer patients.2 3 However, at least
\none in four people needing radiotherapy does not receive it.3
\nThis report aims to demonstrate the significant role of radiotherapy
\nin achieving high?quality cancer care and highlights what needs to be done
\nto close the current gap in utilisation of radiotherapy across Europe.
\nWe call on all stakeholders, with policymakers at the helm, to help position
\nradiotherapy appropriately within cancer policies and models of care
\n? for the benefit of cancer patients today and tomorrow.

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)0.042
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Bibliometrics, Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Meta-epidemiology (narrow), Bibliometrics, Open science, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0420.021
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0130.022
Science and technology studies0.0030.002
Scholarly communication0.0050.003
Open science0.0170.009
Research integrity0.0030.020
Insufficient payload (model declined to judge)0.0060.004

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 head0.463
GPT teacher head0.527
Teacher spread0.064 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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