Bibliographic record
Abstract
This paper develops a framework to compare clinical decision making in relation to chronic and acute medical conditions. Much of the literature on patient-physician decision making has focused on acute and often life-threatening medical situations in which the patient is highly dependent upon the expertise of the physician in providing the therapeutic options. Decision making is often constrained and driven by the overwhelming impact of the acute medical problem on all aspects of the individual's life. With chronic conditions, patients are increasingly knowledgeable, not only about their medical conditions, but also about traditional, complementary, and alternative therapeutic options. They must make multiple and repetitive decisions, with variable outcomes, about how they will live with their chronic condition. Consequently, they often know more than attending treatment personnel about their own situations, including symptoms, responses to previous treatment, and lifestyle preferences. This paper compares the nature of the illness, the characteristics of the decisions themselves, the role of the patient, the decision-making relationship, and the decision-making environment in acute and chronic illnesses. The author argues for a different understanding of the decision-making relationships and processes characteristic in chronic conditions that take into account the role of trade-offs between medical regimens and lifestyle choices in shaping both the process and outcomes of clinical decision-making. The paper addresses the concerns of a range of professional providers and consumers.
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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 | 0.017 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".