An Environmental Scan of the National and Provincial Diagnostic Reference Levels in Canada for Common Adult Computed Tomography Scans
Bibliographic record
Abstract
Several regulatory bodies have agreed that low-dose radiation used in medical imaging is a weak carcinogen that follows a linear, non-threshold model of cancer risk. While avoiding radiation is the best course of action to mitigate risk, computed tomography (CT) scans are often critical for diagnosis. In addition to the as low as reasonably achievable principle, a more concrete method of dose reduction for common CT imaging exams is the use of a diagnostic reference level (DRL). This paper examines Canada's national DRL values from the recent CT survey and compares it to published provincial DRLs as well as the DRLs in the United Kingdom and the United States of America for the 3 most common CT exams: head, chest, and abdomen/pelvis. Canada compares well on the international scale, but it should consider using more electronic dose monitoring solutions to create a culture of dose optimization.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".