The OMEGA-NET International Inventory of Occupational Cohorts
Bibliographic record
Abstract
In a recent count of cohort studies in Europe capturing information on occupation and/or occupational exposures, we estimated that there are more than 60 major studies with some type of occupational information that enrolled over 30 million persons. With few exceptions there have been no large-scale analyses systematically combining cohorts from this extraordinary resource. We present the development of an inventory of cohorts with occupational information in Europe and internationally and describe the online interactive tool with detailed information on existing cohorts. The OMEGA-NET inventory can be accessed at http://occupationalcohorts.net/ includes cohorts, case-control studies nested within cohorts and intervention studies that are active or can substantiate that their data are potentially accessible; that include data on occupation and/or industry or at least one occupational exposure; and that have at least one follow-up, either already conducted or planned. We expect that this open access inventory will be an important prerequisite for use of this resource of existing studies for research and policy development.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.013 |
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".