Bibliographic record
Abstract
STP 1408 examines the latest data and technology on isocyanates, and features topics ranging from sampling and analysis methods to health effects. Isocyanates are widely used in many industrial processes because of their high activity and affinity to many substances, which lead to polymerization, as well as the properties for the resulting polymers. They are used in the production of adhesives, elastomers, binders, flexible or rigid foams, paints, and lacquers. Because these products are used in a large number of synthesis and processing industries, many workers may be at risk of hazardous exposure. In addition, the various chemical and physical states of mixtures of isocyanate monomers and prepolymers make it difficult to document exposure-related toxicity through valid environmental sampling and analysis methods. Therefore it is of the utmost importance that the knowledge and tools necessary for the safe use of these products be made available to provide protection to the worker and the environment. 11 peer-reviewed papers cover: Isocyanate Determination in Atmospheres features new developments in sampling and analysis methods for workplace and environmental monitoring, including direct reading instrumentation, and how they relate to characterization of isocynate monomers and oligomers. Sampling Strategy and Control details case studies; global effects; interpretation of test results; control measures; and personal protective equipment designed to meet compliance. Health Effects covers toxicology; different routes of exposure, such as skin contact as well as inhalation; biological monitoring; surface contamination determination; evaluation of health effects; and the diagnostics used to detect exposure.
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 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) | 0.673 | 0.699 |
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; both teacher heads agree on what is shown here.
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".