CIP10 Optimization for 4,4-Methylene Diphenyl Diisocyanate Aerosol Sampling and Field Comparison With Impinger Method
Bibliographic record
Abstract
4,4-methylene diphenyl diisocyanate (MDI) aerosol exposure evaluation in spray foam insulation application is known as being a challenge because the spray foam application actually involves a fast-curing process. Available techniques are either not user-friendly or are inaccurate or not validated for this application. To address these issues, a new approach using a CIP10M was developed to appropriately collect MDI aerosol in spray foam insulation while being suitable for personal sampling. The CIP10M is a commercially available personal aerosol sampler that has been validated for the collection of microbial spores into a liquid medium. Tributylphosphate with 1-(2-methoxyphenyl)piperazine (MOPIP) was introduced into the CIP10M to collect and stabilize the MDI aerosols. The limit of detection and limit of quantification of the method were 0.007 and 0.024 μg ml(-1), respectively. The dynamic range was from 0.024 to 0.787 μg ml(-1) (with R (2) ≥ 0.990), which corresponds to concentrations in the air from 0.04 to 1.3 µg m(-3), assuming 60 min of sampling at 10 l min(-1). The intraday and interday analytical precisions were <2% for all of the concentration levels tested, and the accuracy was within an appropriate range of 98 ± 1%. No matrix effect was observed, and a total recovery of 99% was obtained. Parallel sampling was performed in a real MDI foam spraying environment with a CIP10M and impingers containing toluene/MOPIP (reference method). The results obtained show that the CIP10M provides levels of MDI monomer in the same range as the impingers, and higher levels of MDI oligomers. The negative bias observed for MDI monomer was between 2 and 26%, whereas the positive bias observed for MDI oligomers was between 76 and 113%, with both biases calculated with a confidence level of 95%. The CIP10M seems to be a promising approach for MDI aerosol exposure evaluation in spray foam applications.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".