Screening Mammography in Older Women: A Pilot Study of Residents' Decisions
Bibliographic record
Abstract
BACKGROUND: Screening mammography is a commonly employed preventive modality. The employment of mammography in older women is not supported by evidence from clinical trials, largely because elderly women were excluded from such trials. Most guidelines do not recommend routine screening in older women. How residents reason in this gray zone has been subject to little empirical study. PURPOSES: This study sought to answer two questions: How variable are residents' decision responses to mammography screening scenarios in older women where there is no clear evidence? What reasons do residents give to justify these decisions? METHODS: Residents were asked to respond to four scenarios and give their screening recommendations and the reasons justifying their decisions. RESULTS: There was considerable variability in resident responses to the four scenarios. Only in one scenario was there near unanimity on the preferred screening decision. Resident perceptions of quality of life, longevity and understanding of the guidelines were cited as justification for their decisions. CONCLUSION: Clinical preceptors should be aware of how the variability of resident perceptions of such factors as quality of life and prognosis may influence decision-making.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".