Bibliographic record
Abstract
Abstract The Estonian Genome Project (EGP) is a large population‐based databank that was established with health records and biological samples from a large portion of the population for use in biomedical and genetic research to improve the future of public health care in Estonia. A nonprofit foundation, the Estonian Genome Foundation presented the EGP to the Estonian government in June 2000 leading to a new legislative act, the “Human Genes Research Act,” that provides a road map for future gene‐related activities and guidelines for the oversight of the databank via a Supervisory Board, Ethics Committee, and Scientific Advisory Board. Unlike other gene discovery efforts, participants in population‐based projects are not selected by specific disease type but rather via a random sampling process. The unbiased nature of the recruitment process provides a more accurate measure of the disease risk provided by particular genetic variants and is anticipated to collect 100,000 samples by the end of 2007. The EGP is part of the first international consortia, P3G, set up between Cart@gene from Canada and GenomEUtwin, a FP5‐funded project coordinated by the University of Helsinki, Finland. With Estonia joining the European Union in 2004, the EGP will also function to build scientific excellence in Estonia. Drug Dev. Res. 62:97–101, 2004. © 2004 Wiley‐Liss, Inc.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.100 | 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".