Bibliographic record
Abstract
Abstract Since the 1980s, it has become recognized by clinicians, researchers, and public health experts that tobacco products are among the most addictive and deadly of all dependence producing substances (Royal College of Physicians 2000; WHO 2001). Nicotine meets all of the standard criteria for a dependence-producing drug and all types of tobacco products are capable of delivering dependence-producing levels of nicotine (US DHHS 1988; Royal Society of Canada 1989; Royal College of Physicians 2000). These conclusions are consistent with the neuropharmacology of nicotine (Henningfield et al. 1996), with clinical studies of nicotine dependence and withdrawal (e.g. Hughes et al. 1990; Henningfield et al. 1995a), and with the epidemiology of tobacco use and dependence (Giovino et al. 1995). In fact, if evaluated against the criteria used to determine the level of psychoactive scheduling set by the U.S. Controlled Substance Act or the World Health Organization’s Convention on Psychotropic Substances (described by McClain and Sapienza 1989; Vocci 1989), nicotine could be appropriately categorized as a controlled substance (Food and Drug Administration 1995, 1996).
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.018 |
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".