Designated smoking areas in streets where outdoor smoking is banned.
Bibliographic record
Abstract
Although Japan has been a signatory to the Framework Convention on Tobacco Control since 2004, progress in translating the recommendations into national policy has been limited. Globally, outdoor smoking bans cover outdoor dining areas, beaches, public parks, schools, etc. In Japan, most of existing outdoor smoking bans allow designated smoking areas (DSAs) in the no-smoking zones, thus limiting protection from second-hand smoke (SHS). We examined the impact of DSAs on air quality in the areas of Kobe City where such ordinance is in force. Air quality measurements were conducted near two DSAs in August 2012 by using personal aerosol monitors. Three measurements were performed, each for 15 minutes, by four investigators: a line-up measurement, a vertical and horizontal measurement, and a circle measurement. In the line-up measurement, over 150 µg/m³ of PM2.5 was detected by the monitor four metres from the ashtray, gradually reducing as the distance increased. In the vertical and horizontal measurement, 80-110 µg/m³ of PM2.5 was detected at 4, 11, 18 and 25 metres. In the circle measurement, similar concentrations of PM2.5 were detected at all testing points (mean concentration 94 µg/m³). The study indicates that DSAs are sources of SHS in zones where a street smoking ban is in force, since SHS spreads widely, both vertically and horizontally. Street smoking bans that permit DSAs strongly limit protection from SHS and should be eliminated if protection against SHS is to be effective where such bans are in force.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".