Proceedings from the 7th Annual University of Calgary Leaders in Medicine Research Symposium
Bibliographic record
Abstract
TOn October 30th, 2015, the Leaders in Medicine (LIM) program at the Cumming School of Medicine, University of Calgary hosted its 7th Annual Research Symposium. Dr. Breanne Everett, President and CEO of Orpyx Medical Technologies and holder both of medical and MBA degrees from the University of Calgary, presented a lecture entitled "Marrying Business and Medicine: Toe-ing a Fine Line". The LIM symposium also provides a forum for both LIM and non-LIM medical students to present their research work in oral and poster presentation formats. This year over 100 students submitted their work and six oral presentations and 99 posters were presented. The oral presentations were as follows: Ryan Lewinson, Prediction of wedged insole-induced changes to knee joint moments during walkingLindsey Logan, Robotic measures provide insight on sensorimotor and cognitive impairments following traumatic brain injury Jackie Mann, What medication information do community doctors want to receive in discharge summaries for safer transfers? Ashley Jensen, Increased mortality associated with resident handoff periods at ten veterans administration medical centers Jason Bau, Keratinocyte growth factor protects against C. difficile-induced cell injury and death Michael Keough, A novel drug class promotes regeneration of central nervous system myelin by overcoming inhibitory scar molecules in vitro and in vivo For further details on the University of Calgary Leaders in Medicine Program see "A Prescription that Addresses the Decline of Basic Science Education in Medical School" (Clinical and Investigative Medicine. 2014;37(5):E29). The LIM Symposium has the following objectives: (1) to showcase the variety of projects undertaken by students in the LIM Program as well as University of Calgary medical students; (2) to encourage medical student participation in research and special projects; (3) to inform students and faculty about the diversity of opportunities available for research and special projects during medical school and beyond; and, (4) to enhance student and staff interactions, with the ultimate goal being to enhance translational medicine improve health.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.147 | 0.047 |
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".