Proceedings of the Hydrogen Sulfide Health Research and Risk Assessment Symposium October 31-November 2, 2000
Bibliographic record
Abstract
The Hydrogen Sulfide Health Research and Risk Assessment Symposium came about for several reasons: (1) increased interest by the U.S. Environmental Protection Agency (EPA) and several state agencies in regulating hydrogen sulfide (H2S); (2) uncertainty about ambient exposure to H2S; (3) confusion and disagreement in the literature about possible health effects at low-level exposures; and (4) presentation of results of a series of recent animal bioassays. The American Petroleum Institute (API) proposed this symposium and the EPA became an early co-sponsor, with the Chemical Industry Institute of Toxicology (CIIT) and the American Forest & Paper Association (AF&PA) contributing expertise and funding assistance. The topics covered in this symposium included Animal Research, Human Research, Mode-of-Action and Dosimetry Issues, Environmental Exposure and Monitoring, Assessment and Regulatory Issues, and closed with a panel discussion. The overall goals of the symposium were to: gather together experts in H2S health effects research and individuals from governmental agencies charged with protecting the public health, provide a venue for reporting of recent research findings, identify gaps in the current information, and outline new research directions and promote research collaboration. During the course of the symposium, presenters provided comprehensive reviews of the state of knowledge for each topic. Several new research proposals discussed at the symposium have subsequently been initiated. This report provides a summary of the talks, poster presentations, and panel discussions that occurred at the Hydrogen Sulfide Health and Risk Assessment Symposium.
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 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.077 | 0.030 |
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".