From Community Genetics to Community Genomics: The Quebec Experience
Bibliographic record
Abstract
Optimal health care delivery requires an understanding of genetic diversity and its associated risks. Population genomics is a rapidly emerging field that will yield such knowledge. As we are entering the genomic era, the need to develop policies and strategies integrating genetic determinants of health into medical services, health promotion and disease prevention is becoming increasingly important, perhaps inevitable. To this end, the Quebec Network of Applied Genetic Medicine (RMGA) supports a multidisciplinary and integrative research strategy which combines Quebec’s expertise in population and community genetics. The present article briefly describes two projects developed with a view to foster such strategy. The ECOGENE-21 project is designed to develop and evaluate resources and strategies for integrating and transferring new knowledge of the human genome to individuals, families and communities. ECOGENE-21 will be capitalizing on another project called CART@GENE, which is generating a combined genetic and demographic map containing information on allelic variation in the subpopulations of Quebec. These two projects are complementary and will be integrated with the ultimate goal of transferring knowledge gained from basic research, to promote health improvement and disease prevention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".