An investigation of videoconferenced geriatric medicine grand rounds in Alberta
Bibliographic record
Abstract
Geriatric medicine grand rounds (GMGR) from the University of Alberta are videoconferenced weekly to health-care providers at up to 9 urban and 14 rural sites across Alberta. A questionnaire was given to all participants attending 20 consecutive GMGR presentations from January 2002. The response rate was 85% (n = 625) for all participants and 99% (n = 123) for physicians alone. The audience was composed of registered nurses (42%), physicians (17%) and other health-care professionals. 'Interest in topic' was cited by 95% as the main reason for attendance. Doctors and nurses cited continuing medical education as an additional factor. The highest attendance was for the topics vascular dementia, behavioural problems in dementia, the genetics of dementia and falls prevention. Participants at the remote sites gave lower evaluations of quality of the GMGR presentations than those at the hub site. The measurement, care and treatment of dementia appeared to be the main concerns of health-care providers across the province. The videoconferencing of GMGR appears to be an effective method of meeting the demands of physicians and allied health professionals for education in geriatric medicine.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".