Use of the Novel Derivatizing Agent 1,8-Diaminonapthalene With the CIP10 Sampler to Measure 4,4’-Methylene Diphenyl Diisocyanate Atmospheres
Bibliographic record
Abstract
DAN is a novel derivatizing agent for isocyanate sampling which targets total reactive isocyanate group (TRIG). Field evaluations have been conducted for 4,4'-Methylene diphenyl diisocyanate (MDI) sampling using DAN as the derivatizing agent in a CIP10. The perimidone formed, selective of TRIG, was analyzed in laboratory by liquid chromatography coupled to tandem mass spectrometry. Workplaces using MDI-based polyurethane spray foam and MDI wood product binder were studied. Each study compared the data obtained between the CIP10/DAN, the CIP10/MP, and a reference method. As a first evaluation, the CIP10/DAN sampled simulated MDI spray foam atmosphere in parallel with impingers (reference method) and CIP10/MP. The mean of the TRIG concentration values measured was 16% (95% confidence interval [CI], [1, 31]) higher for the CIP10/MP samples as compared to the impinger samples, while the mean TRIG concentrations found were 98% (95% CI [63, 133]) higher for the CIP10/DAN samples as compared to the impinger samples. For sampling done in a real workplace using MDI-based spray foam, the CIP10/DAN method showed lower results than the CIP10/MP method. The presence of hygroscopic DMSO used in the DAN approach is a limitation and may prevent obtaining accurate results in the spray foam atmosphere. CIP10/DAN was also studied in MDI wood product binder atmosphere. Mean TRIG concentrations found were 80% (95% CI [51, 110]) and 79% (95% CI [50, 108]) lower for the CIP10/MP and CIP10/DAN method, respectively, as compared to the reference method (a 13-mm filter coated with MP). In this case, the CIP10 may have reached its limit in this last evaluation where vapors and particles below 1 µm were not collected as efficiently as they were with the reference method.
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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 | 0.001 | 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 | 0.001 | 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".