Relationship between phantom failure rates and radiation dose in mammography accreditation
Bibliographic record
Abstract
The American College of Radiology Mammography Accreditation Program (ACR MAP) reviews both clinical mammograms and a phantom image to assess clinical and technical quality from each mammography unit. The phantom contains details representing fibers (speculations), speck groups (microcalcifications), and masses. The depiction of these structures by the mammographic system is scored by medical physicists. The phantom image is taken using the facility's exposure technique for a 4.2-cm thick breast of average composition. The mean glandular dose (MGD) is determined from a set of thermoluminescent dosimeters placed on top of the chest wall edge of the phantom. Phantom scores and MGD data collected from 1993 to 1999 based on 31 535 unit evaluations are presented in this paper. The relationship between the failure rate for phantom image quality and MGD has been analyzed. While over all doses the phantom failure rate was 11%, for doses of 0.26 to 0.50 mGy the failure rate was 43%. The phantom failure rate fell continuously to about 6% for MGDs in the range of 1.51-2.0 mGy. With further increases in dose, failure rates began to rise. Factors that may account for these results are presented and discussed.
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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 | 0.010 | 0.091 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".