Carbonyls emissions in different brands and flavours of heated tobacco products
Bibliographic record
Abstract
Heated tobacco products have been launched in a variety of brands and flavours; however, published data covering carbonyl emissions not cover all the different brands and flavours. This work focuses on the carbonyls emissions from 5 heated tobacco products (HTPs) brands: IQOS, LIL, PULZE, ILUMA and GLO and 3 different flavours per brand (IQOS and ILUMA:Yellow Selection-Silver Selection-Turquoise Selection, LIL: Regular-Marine-Roxo, PULZE: Rich Bronze-Ice-Capsule Polar and GLO: Classic Tobacco-Arctic Click-Scarlet Click), under ISO and Health Canada Intense (HCI/CAN) puffing regimes. The carbonyls are collected in an acidified DNPH solution and analyzed by HPLC-UV. Seven carbonyls were detected: Formaldehyde, Acetaldehyde, Propionaldehyde, Butyraldehyde and Crotonaldehyde and Acrolein/Acetone together. The results (Fig 1, Fig 2) show that the HCI/CAN puffing regime leads in general to an increase in carbonyls emissions. Acetaldehyde is the dominant carbonyl, followed by Propionaldehyde, Butyraldehyde, Formaldehyde and Crotonadehyde. The impact of the brand is more significant comparing to the flavour. Fig 1. Emission of acetaldehyde erj;64/suppl_68/PA4032/F1 F1 F1 Fig 2. Emission of propionaldehyde erj;64/suppl_68/PA4032/F2 F2 F2
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.004 | 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".