Results of the Year 2000 Abdomen Task Survey of the American Registry of Diagnostic Medical Sonographers
Bibliographic record
Abstract
The authors' purpose was to evaluate the current practice of registered diagnostic medical sonographers, with specialty in abdomen, of the American Registry of Diagnostic Medical Sonographers (ARDMS).A randomized sample of 2350 registered diagnostic medical sonographers with specialty in abdomen were chosen from the ARDMS database to complete a task survey on the Internet.The survey consisted of a 235-item ques tionnaire with regard to demographics, education, and frequency of specific sonograms performed in daily practice.Compared with the 1994 survey, registrants have received more formal education and less on-the-job training. Traditional tasks remain the predominant responsibilities of registered diagnostic medical sonographers with specialty in abdomen, including liver, biliary system, gallbladder, kidney, and pancreas, but a small minority of sonographers also perform liver transplant, kidney transplant, trauma, and musculoskeletal sonograms, and use newer technologies, such as power Doppler and tissue harmonic sonography, as well as transrectal sonography.The authors conclude that the ARDMS abdomen examination reflects current practice, but future revisions should include a small percentage of items in these newer areas.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".