Bibliographic record
Abstract
OBJECTIVES: Prospect theory (PT) hypothesizes that people judge states relative to a reference point, usually assumed to be their current health. States better than the reference point are valued on a concave portion of the utility function; worse states are valued on a convex portion. Using prospectively collected utility scores, the objective is to test empirically implications of PT. METHODS: Osteoarthritis (OA) patients undergoing total hip arthroplasty periodically provided standard gamble scores for three OA hypothetical states describing mild, moderate, and severe OA as well as their subjectively defined current state (SDCS). Our hypothesis was that most patients improved between the pre- and postsurgery assessments. According to PT, scores for hypothetical states previously > SDCS but now < SDCS should be lower at the postsurgery assessment. RESULTS: Fourteen patients met the criteria for testing the hypothesis. Predictions were confirmed for 0 patients; there was no change or mixed results for 6 patients (42.9 percent); and scores moved in the direction opposite to that predicted by PT for 8 patients (57.1 percent). CONCLUSIONS: In general, the direction and magnitude of the changes in hypothetical-state scores do not conform to the predictions of PT.
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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 | 0.029 | 0.211 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 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 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".