[Review on the evaluation research of the effects of smoke-free legislations on cardiovascular diseases].
Bibliographic record
Abstract
A substantial amount of data suggested that exposure to secondhand smoke (SHS) could cause cardiovascular diseases and acute coronary events in nonsmoking adults. In order to protect the public from SHS, more and more countries and regions across the world have enacted and implemented smoke-free legislations. Developed countries, such as USA, Canada, the Great Britain, Ireland, Italy and Spain, have carried out many studies to analyze the effects of smoke-free legislations on the hospital admission, incidence and mortality of cardiovascular diseases with the purpose of confirming the health benefits of the smoking ban and promoting the conduct of the ban. We searched PubMed, EMBASE, Web of Science, Cochrane Library,China National Knowledge Infrastructure(CNKI),WANFANG databaseto summarize the study designs, evaluating indicators, statistical methods and results of these studies to provide reference for evaluating smoke-free legislations in inland cities in China.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".