Medical expert opinion and judge's discretion in medical lawsuits:which will be decisive?
Bibliographic record
Abstract
In the field of medical lawsuits,medical expert testimony or common practice is strong evidence,but not a conclusive one. The famous Bolam case seems to deem common practice in medical profession as conclusive one. The Bolam test is not only applied in treatment cases but also is extended to diagnosis and informed consent cases. But this test is not recognized in Australia and Canada. In Bolitho case,the judicial opinion in UK changed,making it more similar to that of Australia and Canada. In this case the judge specifically emphasized that the medical opinion should have a logical basis,reasonable and respectable. The judge can learn to utilize risk-benefits analysis to make their own decision in particular cases.
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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 | 0.050 | 0.212 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.025 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.029 | 0.014 |
| Insufficient payload (model declined to judge) | 0.011 | 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".