A Clinical Consensus Approach to Developing a New Funding Model for Radiation Services in Ontario
Bibliographic record
Abstract
In 2021, Ontario Health (Cancer Care Ontario) introduced a quality-based procedure model for the funding of radiation treatment (RT) in Ontario. This model ties reimbursement to patient care activities, ensuring equity and transparency in funding. Over 200 RT interprofessionals (oncologists, therapists and physicists) participated on 22 expert panels to establish or identify 288 evidence-based RT protocols and 672 quality expectations (QEs) to optimally deliver RT, which eventually led to the micro-costing of all protocols. Iterative review is required to ensure updated techniques and identify evolving standards of care, thereby providing the highest quality of RT care to Ontarians.
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 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 | 0.260 | 0.173 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.020 | 0.018 |
| Scholarly communication | 0.018 | 0.011 |
| Open science | 0.011 | 0.018 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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.
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".