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
PURPOSE: Risk communication is an integral aspect of shared decision-making and evidence-based patient choice. There is currently no recommended way of communicating risks and benefits of cataract surgery to patients. This study aims to investigate whether the way this information is presented influences patients' perception of how risky surgery will be. METHODS AND ANALYSIS: Two-arm parallel randomised study and patients referred for cataract surgery were assigned to receive information framed either positively (99% chance of no adverse effects) or negatively (1% chance of adverse effects). Subsequently, patients rated their perceived risk of experiencing surgical side effects on a 1-6 scale. RESULTS: This study included 100 patients, 50 in each study group. Median (IQR) risk perception was 2 (1-2) in the positive framing group and 3 (1-3) in the negative framing group (p<0.0001). Risk framing was the only factor that was significant in risk perception, with no differences found by other patient clinical or demographic characteristics. CONCLUSION: Patients who received positive framing reported lower risk scores for cataract surgery than patients who received negative framing. Patient factors were not identified as significant determinants in patients' perceived risk. Larger longitudinal studies are warranted to further investigate.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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