American College of Radiology Imaging Network Digital Mammographic Imaging Screening Trial: Objectives and Methodology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study was approved by the Institutional Review Board (IRB) of the American College of Radiology Imaging Network (ACRIN) and each participating site and by the IRB and the Cancer Therapy Evaluation Program at the National Cancer Institute. The study was monitored by an independent Data Safety and Monitoring Board, which received interim analyses of data to ensure that the study would be terminated early if indicated by trends in the outcomes. The ACRIN, which is funded by the National Cancer Institute, conducted the Digital Mammographic Imaging Screening Trial (DMIST) primarily to compare the diagnostic accuracy of digital and screen-film mammography in asymptomatic women presenting for screening for breast cancer. Over the 25.5 months of enrollment, a total of 49 528 women were included at the 33 participating sites, which used five different types of digital mammography equipment. All participants underwent both screen-film and digital mammography. The digital and screen-film mammograms of each subject were independently interpreted by two radiologists. If findings of either examination were interpreted as abnormal, subsequent work-up occurred according to the recommendations of the interpreting radiologist. Breast cancer status was determined at biopsy or follow-up mammography 11-15 months after study entry. In addition to the measurement of diagnostic accuracy by using the interpretations of mammograms at the study sites, DMIST included evaluations of the relative cost-effectiveness and quality-of-life effects of digital versus screen-film mammography. Six separate reader studies using the de-identified archived DMIST mammograms will also assess the diagnostic accuracy of each of the individual digital mammography machines versus screen-film mammography machines, the effect of breast density on diagnostic accuracy of digital and screen-film mammography, and the effect of different rates of breast cancer on the diagnostic accuracy in a reader study.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it