Bibliographic record
Abstract
This study examines the occurrence of organophosphate esters (OPEs) in cigarettes and sidestream cigarette smoke and to see the OPE formation characteristics during smoking. All seven OPEs in both gas and particulate phases were measured in sidestream cigarette smoke for four brands of cigarettes. Tributyl phosphate (TBP), tris(2-butoxyethyl) phosphate (TBEP), tris(2-chloroethyl) phosphate (TCEP), and triphenyl phosphate (TPP) were found frequently. Median total OPE increases in the air samples during smoking were 56.2 ng per cigarette for gas-phase OPEs and 2360 ng per cigarette for particulate-phase OPEs. TBP and TCEP could be absorbed to particles in air more readily than alkans as seen from the correlation line between gas–particle partition coefficients (Kp) and the subcooled liquid vapor pressures (PLº) for alkans. Furthermore, TBP was determined in the cigarettes. Median total OPE decreases in the cigarette samples during smoking were 1200 ng per cigarette. The combustion reaction increased TBP and TBEP levels in cigarettes, and particulate-phase TBEP in air appeared to influence the production of TBP, TCEP, and TPP. TBP and TBEP in cigarettes likely affect the production of TBP, TBEP, TCEP, and TPP in air during smoking.
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 | 0.001 |
| 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 | 0.000 | 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".