Towards dose reduction in CT: patient radiation dose assessment for CT examinations at university health center in Canada and comparison with national diagnostic reference levels
Bibliographic record
Abstract
Dose indicators such as the computed tomography dose index (CTDI) and dose-length product (DLP) were gathered for all routine abdomen-pelvis, chest and head examinations performed on all computed tomography (CT) scanners at a University Health Center (UHC) in Canada. These indicators were analysed and compared with the range of diagnostic reference levels (DRLs) suggested by Health Canada and with DRLs in other countries. Mean DLP values varied from one scanner to another, but mean values at the UHC (750 mGy cm(-1) for abdomen-pelvis CT, 349 mGy cm(-1) for chest CT and 1181 mGy cm(-1) for head CT) were all below the upper limit of the range of DRLs suggested by Health Canada. Local DRLs at the UHC were set to 810 mGy cm(-1) for abdomen-pelvis CT, 345 mGy cm(-1) for chest CT and 1205 mGy cm(-1) for head CT. Results, however, show the need for protocols revisions, since some scanners exhibit mean DLP values slightly below or above the upper limit of the range of DRLs suggested by Health Canada.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".