Proceedings of the Canadian Society for Molecular Biosciences (CSMB) 2024 Conference — Gene Regulation: From Cells to Systems
Bibliographic record
Abstract
The 67th Canadian Society for Molecular Biosciences (CSMB) Annual Conference took place in Winnipeg, Manitoba, from 6 May to 8 May 2024, at the University of Manitoba, Winnipeg. The conference theme "Gene Regulation: From Cells to Systems" was selected to reflect the breadth and multidisciplinary nature of CSMB's membership and to facilitate interactions among scientists and researchers across different disciplines and with diverse research programs and approaches. This meeting attracted registered participants from provinces across Canada and the USA. The objective of this meeting was to promote the inclusive dissemination, conversation, and discussions of molecular biosciences research, in different areas of molecular biosciences covering a wide range of topics in basic science and health-related research subjects such as neuroscience, cancer biology, immunology, physiology, bacterial systems, RNA biology, protein homeostasis, cellular metabolism and cell death mechanisms, neurobiology and neurogenetics, epigenetics, chromatin biology, environmental influence, stem cell biology, and genome-wide studies. This meeting provided a discussion opportunity for molecular bioscience researchers to develop innovative and novel strategies and collaborations for biomedical and translational research.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.050 | 0.009 |
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".