Adult Attention Deficit-Hyperactivity Disorder & smoking : an overview of epidemiological data, a review of current studies and the need for future research in Northwestern Ontario / by Nelson Sidorski.
Bibliographic record
Abstract
This research project was designed to provide a summary of the studies related to \nadult ADHD and smoking, and utilize these findings to improve future research about \nadult ADHD and smoking in Northwestern Ontario. The project is split into three main \nsections: 1) The Epidemiology of ADHD, Smoking, and Substance Abuse Among the \nUnited States, Canada, Ontario and Thunder Bay; 2) Adult ADHD & Smoking: A \nReview of the Literature; and, 3) Paving the Way for Research in ADHD and Smoking in \nNW Ontario. A literature review was conducted for each particular section including a \nsearch of relevant English databases as well as the grey literature. A more detailed \nexplanation of the methods used can be found in the beginning of each section. \nOverview of Section 1: The Epidemiology of ADHD, Smoking, and Substance Abuse \nAmong the United States, Canada, Ontario and Thunder Bay
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.017 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".