176: Measuring Uptake of the Canadian Partnership for Quality Radiotherapy (CPQR) Programmatic Key Quality Indicators (KQI): A Pan-Canadian Audit of Compliance
Bibliographic record
Abstract
reliable communication and consistent goals.The second challenge was to provide a province-wide repository for sharing information and facilitating communication.In parallel with addressing these challenges, developmental work on streamlining and standardizing the RT process occurred.Results: The initial SC was assembled in Q1 2015; and full assembly of the SC and CG was completed in Q1 2016.The CG meets virtually on a weekly basis.The SC meets every ~6 weeks.Every second SC meeting is face-to-face at alternating RT centre locations.A Sharepoint site, accessible both inside and outside the organizational network, provides a central repository for information.RT process developments to-date include: 1) standard use of ARIA RO V11 MR 5.2 Prescribed Treatment workspace; 2) the entry of Diagnosis and Staging in ARIA RO; 3) standard definitions for a number of variables in our provincial minimum dataset; and 4) generation of an End of Treatment summary in ARIA RO with future distribution to other systems. Conclusions:The participation of all disciplines and facilities involved in the radiotherapy process is essential.Collaboration and communication between the four RT centres has greatly improved because of this project.North and South ARIA RO are now utilizing the same software versions and are converging in processes, carepaths, and definitions.The SC and CG provide a radiation oncology voice for communication with other provincial cancer control and healthcare initiatives.
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 | 0.017 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".