Determination of “Hoffmann Analytes” in Cigarette Mainstream Smoke. The Coresta 2006 Joint Experiment
Bibliographic record
Abstract
Abstract Regulatory authorities are currently discussing the measurement of and imposition of ceilings on certain smoke analytes, the so called ‘Hoffmann analytes’. However, as a pre-requisite, the measurement methods and the tolerances around the measurements first need to be established. In 1999, the Cooperation Centre for Scientific Research Relative to Tobacco (CORESTA) set up a Task Force ‘Special Analytes’ to deal with analytical methodology for measuring ‘Hoffmann analytes’ under International Standard (ISO) smoking and to work towards the standardisation of methods. This paper describes the output and conclusions from a 2005-2006 joint experiment made within the Task Force representing laboratories currently able to analyse these compounds. Data were obtained on most ‘Hoffmann analytes’ from reference cigarettes (2R4F and 1R5F), collecting data according to the existing methods used by the nineteen participating laboratories, in order to describe the within and among laboratory variability and to see which methods could most benefit from more rigorous standardisation work. In some cases, the applied statistical analysis found that methods could not well differentiate the 1R5F and 2R4F cigarettes of differing ‘tar’ yield. This was explained, in part, by the broad range of methods used by the participating laboratories but also indicated that there were significant inadequacies in the choice of some methods or weaknesses in their application. Results indicate that ‘Hoffmann analyte’ data are generally more variable both within and among laboratories than nicotine free dry particulate matter (NFDPM); nicotine and carbon monoxide due to their lower smoke yields. Accordingly, tolerances around methods adopted for regulatory purposes will need to be proportionately higher. Methods for benzo[ a ]pyrene (B[ a ]P) and tobacco-specific nitrosamines (TSNAs), already taken to CORESTA recommended methods or ISO standardised methods through the efforts of this Task Force, give some of the most reproducible results, showing the value of this process. However, these data strongly suggest that even these analytes have much higher among-laboratory variability than for NFDPM, nicotine and CO and, based on the only two available one point in time studies, may need tolerances in the range of 35-45% for B[a]P and 26-55% for TSNAs, if they are to be measured for regulatory purposes. The collected data is useful to participating laboratories for internal method validation and laboratory accreditation, and data comparisons with others allow laboratories to identify strengths and weaknesses in their current methods. However, much work still needs to be carried out to take most of the methods towards standardisation. Although some fundamental differences or areas of concern around the methodology are discussed herein, they are not comprehensive and there may be others that need to be addressed before methods can be considered ready to take to a Recommended Method and/or to an ISO Standard. These methodological issues are being addressed in further CORESTA work within this Task Force. Smoke analytes with the highest variability found in this study and those analytes that are currently of highest regulatory interest are being prioritised and after further joint experiments, the results are intended to be published.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".