© 2000 Canadian Medical Association or its licensors
Bibliographic record
Abstract
In the face of a civil suit or a college disciplinary hearing,many physicians simply don’t know what to do. “Some be-come devastated, ” says Dr. Stanley Kolber. He ought to know. Not only is Kolber a lawyer and a physician, he’s also in charge of Alberta’s new Medical-Legal Peer Support Network, the first of its type in Canada. And he’s seen it all. “Those who don’t know what to do — their practices fall apart, their families fall apart, their lives fall apart, ” says Kol-ber. “This [support network] allows them to put it back to-gether. ” It also helps those who are merely overwhelmed by the stress created by the legal process. The network, a new effort by the Alberta Medical Associ-ation’s Physicians ’ Assistance Committee, was launched Mar. 1 by 10 volunteers who have themselves been through legal or disciplinary proceedings. “They have a feel for what’s in-
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How this classification was reachedexpand
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 | 0.002 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.900 | 0.154 |
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; both teacher heads agree on what is shown here.
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".