Radiotherapy: Seizing the opportunity in cancer care
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.059 | 0.010 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".