Bibliographic record
Abstract
This is the first study to systematically track the tobacco use prevalence in an entire emergency department (ED) population and compare age-stratified rates to the general population using national, provincial, and regional comparisons. A tobacco use question was integrated into the ED electronic registration process from 2007 to 2010 in 11 northern hospitals (10 rural, 1 urban). Results showed that tobacco use documentation (85-89%) and tobacco use (26-27%) were consistent across years with the only discrepancy being higher tobacco prevalence in 2007 (32%) due to higher rates at the urban hospital. Age-stratified outcomes showed that tobacco use remained high up to 50 years old (36%); rates began to decrease for patients in their 50's (26%) and 60's (16%), and decreased substantially after age 70 (5%). The age-stratified ED tobacco rates were almost double those of the general population nationally and provincially for all but the oldest age groups but were virtually identical to regional rates. The tobacco use tracking and age-stratified general population comparisons in this study improves on previous attempts to document prevalence in the ED population, and at a more local level, provides a "big picture" overview that highlights the magnitude of the tobacco-use problem in these communities.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".