Sci‐Fri AM: Quality, Safety, and Professional Issues 01: CPQR Technical Quality Control Suite Development including Quality Control Workload Results
Bibliographic record
Abstract
A close partnership between the Canadian Partnership for Quality Radiotherapy (CPQR) and the Canadian Organization of Medical Physicist's (COMP) Quality Assurance and Radiation Safety Advisory Committee (QARSAC) has resulted in the development of a suite of Technical Quality Control (TQC) Guidelines for radiation treatment equipment, that outline specific performance objectives and criteria that equipment should meet in order to assure an acceptable level of radiation treatment quality. The framework includes consolidation of existing guidelines and/or literature by expert reviewers, structured stages of public review, external field‐testing and ratification by COMP. The adopted framework for the development and maintenance of the TQCs ensures the guidelines incorporate input from the medical physics community during development, measures the workload required to perform the QC tests outlined in each TQC, and remain relevant (i.e. “living documents”) through subsequent planned reviews and updates. This presentation will show the Multi‐Leaf Linear Accelerator document as an example of how feedback and cross‐national work to achieve a robust guidance document. During field‐testing, each technology was tested at multiple centres in a variety of clinic environments. As part of the defined feedback, workload data was captured. This lead to average time associated with testing as defined in each TQC document. As a result, for a medium‐sized centre comprising 6 linear accelerators and a comprehensive brachytherapy program, we evaluate the physics workload to 1.5 full‐time equivalent physicist per year to complete all QC tests listed in this suite.
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 | 0.030 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.115 | 0.071 |
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".