Bibliographic record
Abstract
The objective of the study was to examine whether cold climate is associated with poorer health in diverse Arctic populations. With climate change increasingly affecting the Arctic, the association between climate and population health status is of public health significance. The mean January and July temperatures were determined for 27 Arctic regions based on weather station data for the period 1961-1990 and their association with a variety of health outcomes assessed by correlation and multiple linear regression analyses. Mean January temperature was inversely associated with infant and perinatal mortality rate, age-standardized mortality rate from respiratory diseases, and age-specific fertility rate for teens and directly associated with life expectancy at birth in both males and females, independent of a variety of socioeconomic, demographic, and health care factors. Mean July temperature was also associated with infant mortality and mortality from respiratory diseases, and with total fertility rate. For every 10 degrees C increase in mean January temperature, the life expectancy at birth among males increased by about 6 years and infant mortality rate decreased by about 4 deaths/1,000 livebirths. Cold climate is significantly associated with higher mortality and fertility in Arctic populations and should be recognized in public health planning.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".