Bibliographic record
Abstract
OBJECTIVE: To determine the role of environmental pollutants in the etiology of nasal polyposis. DESIGN: Case-control study. SETTING: A community-based hospital practice in the Gaspesian peninsula in rural northeastern Quebec. PATIENTS: Fifty-five case patients with nasal polyposis and 55 age-matched control subjects without nasal polyposis who were seen at one physician's practice (J.K.) from March 1, 1998, to December 19, 1998. INTERVENTIONS: Exposure to woodstoves, indoor tobacco smoke, and pets and occupational exposures to noxious inhalant compounds. RESULTS: Forty-five (82%) of the cases, but only 14 (25%) of the controls, reported using woodstoves, yielding a crude odds ratio (OR) of 13.1. The corresponding risk associated with occupational exposure to noxious inhalant compounds was also high (OR, 6.1). When adjusted in various ways for the presence of other factors, these ORs remained high and statistically significant. For woodstove use, the point estimates of the ORs were consistently above 10, with the lower limits of 95% confidence intervals above 5. For occupational exposures to noxious inhalant compounds, the various adjusted OR estimates were above 6, with the lower limits above 1.5. CONCLUSIONS: There is a strong association between the use of woodstoves as a principal source of heating and the development of nasal polyposis. Occupational exposures to noxious inhalant compounds (other than tobacco smoke) also play an important role in its etiology.
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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".