Knowledge on health effects and practices of smoking among the smokers in the Eastern Terai Region of Nepal
Bibliographic record
Abstract
Tobacco smoking kills more than five million people a year worldwide. According to Nepal Adolescent and Young Adult (NAYA) Survey 2000, about one quarter of young boys and one in 10 girls have smoked tobacco at some time or the other. A cross sectional study was done in Jalthal & Maheshpur Village Development Committee of Jhapa district using simple random sampling method among 200 participants. Interview methods with semi-structured questionnaires were used as tool for data collection. The objective of this study was to identify the reason of initiation of smoking, explore the pattern of smoking and to assess the health knowledge among the smokers regarding effect of smoking. It was reported that, 63% of them started to smoke at the age of 10-19 years. Most smokers were male, illiterate, unemployed and fell below the poverty line. Though most of the smokers knew the ill effect due to smoking; habituation was the main reason for not being able to stop smoking and 10% of them smoked for recreation. DOI: http://dx.doi.org/10.3126/jcmc.v4i1.10843 Journal of Chitwan Medical College 2014; 4(1): 22-25
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".