Inhaled Formaldehyde: Exposure Estimation, Hazard Characterization, and Exposure-Response Analysis
Bibliographic record
Abstract
Formaldehyde has been assessed as a Priority Substance under the Canadian Environmental Protection Act. Probabilistic estimates of exposure of the general population in Canada to formaldehyde in ambient and indoor air are presented. Critical health effects include sensory irritation and the potential to induce tumors in the upper respiratory tract (the nasal region in rodents and potentially the lungs of humans). The majority of the general population is exposed to airborne concentrations of formaldehyde less than those typically associated with sensory irritation (i.e., 0.1 mg/m3). Based primarily upon data derived from laboratory studies, the inhalation of formaldehyde under conditions that induce cytotoxicity and sustained regenerative proliferation within the respiratory tract is considered to present a carcinogenic hazard to humans. At airborne levels for which the prevalence of sensory irritation is minimal (i.e., 0.1 mg/m3), risks of respiratory-tract cancers for the general population estimated on the basis of a biologically motivated case-specific model are exceedingly low. This biologically motivated case-specific model incorporates two-stage clonal expansion and is supported by dosimetry calculations from computational fluid dynamics analyses of formaldehyde flux in various regions of the nose and single-path modeling for the lower respiratory tract. The degree of confidence in the underlying database and uncertainties in estimates of exposure and in characterization of hazard and dose response are delineated.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".