Sci—Thur PM: Imaging — 06: Canada's National Computed Tomography (CT) Survey
Bibliographic record
Abstract
The value of computed tomography (CT) in medical imaging is reflected in its' increased use and availability since the early 1990's; however, given CT's relatively larger exposures (vs. planar x‐ray) greater care must be taken to ensure that CT procedures are optimised in terms of providing the smallest dose possible while maintaining sufficient diagnostic image quality. The development of CT Diagnostic Reference Levels (DRLs) supports this process. DRLs have been suggested/supported by international/national bodies since the early 1990's and widely adopted elsewhere, but not on a national basis in Canada. Essentially, CT DRLs provide guidance on what is considered good practice for common CT exams, but require a representative sample of CT examination data to make any recommendations. Canada's National CT Survey project, in collaboration with provincial/territorial authorities, has collected a large national sample of CT practice data for 7 common examinations (with associated clinical indications) of both adult and pediatric patients. Following completion of data entry into a common database, a survey summary report and recommendations will be made on CT DRLs from this data. It is hoped that these can then be used by local regions to promote CT practice optimisation and support any dose reduction initiatives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".