Environmental Toxicology and Risk Assessment: Science, Policy, and Standardization—Implications for Environmental Decisions: Tenth Volume
Bibliographic record
Abstract
Description The latest volume in this ASTM series explores the advancements in the field of environmental toxicology and risk assessment, including methods of carrying scientific findings forward to sound policy decisions. 25 papers in 6 sections cover: Aquatic Toxicology--examines the ionic composition in water used in toxicity tests and how that impacts on metal toxicity; how modified PAHs impact on EROD levels; how UV radiation in natural aquatic settings impacts on photosynthesis in phytoplankton; and ship channel contaminant assessment. Interface Between Policy, Science and Risk Assessment--addresses the use appropriate data in environmental modeling; statistical procedures to find the real ecological risk drivers; comparisons of fish and human toxicity; and statistical evaluation of terrestrial non-target organisms. ASTM Standards and Their Applications--focuses on how ASTM standards can be used in science and policy. Biomonitoring of Sediments and Aquatic Systems--deals with an extension of the Microtox assay; assessing PAH bioavailability at off-shore oil wells; a new powerful molecular bioindicator; a comparison of EROD and fibronectin levels; and toxicity of photomodified polycyclic aromatic hydrocarbon mixtures in contaminated sediments. Current Issues In Soil Toxicity and Remediation--discusses how important the evaluation of soil toxicity is becoming, and how such contaminated sites can be cleaned for reuse. New Directions in Environmental Assessment and Recovery--explores how to use environmental assessment data to make decisions on risk and restoration.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.050 | 0.036 |
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".