Addressing the need for a new generation of young translational researchers that focuses on societal impact: The Apollo Toronto Story
Bibliographic record
Abstract
Translational research (TR) is a multidirectional and multidisciplinary integration of basic research, patient-oriented research and population-based research, with the long-term goal of improving human health. Unfortunately, the current scientific training system does not adequately align with the goals of TR. To address this issue, an organization called Apollo Toronto was established at the University of Toronto in Toronto, Ontario. Apollo Toronto is a medical student-run international collaborative project between the Eureka Institute for Translational Medicine and the University of Toronto (one of Eureka Institute’s partner universities), and provides a general overview of TR to interested medical and graduate students. Through local and international initiatives, the various Apollo chapters (including Apollo Toronto) aim to establish a network of trainees equipped to address systemic issues that impede the translation of an ever-growing body of scientific literature into health solutions.
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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 | 0.042 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.026 |
| Scholarly communication | 0.018 | 0.013 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.021 | 0.036 |
| Insufficient payload (model declined to judge) | 0.008 | 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".