The Analysis of Cumulative Influence of Factors of Environment on a State of Health of the Population of Vladimir Region
Bibliographic record
Abstract
There was investigated the contribution of factors of environment to formation of health for adult population on indicators of mid-annual rates of growth/decrease of disease of system of blood circulation and of some interfaced nosology on an example of the population of Vladimir region. The differential criterion of primary disease of system of blood circulation is considered as an indicator, integrally reflecting degree of adaptation to environment conditions on population and suitable for construction short-term prognostic estimations. It is shown that business factors or the factors of a standard of living characterized by economic indicators, are leading risk factors in disease of system of blood circulation in Vladimir region which contribution is estimated by size of 38%. With use of regressive equations were received look-ahead estimations of annual rates of primary disease of system of blood circulation. In the regional centre Vladimir was observed more intense situation on rates of disease of system of blood circulation, than in Vladimir region.
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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 | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".