Hazard assessment of oil spill response chemical herding agents to commercially valuable North Atlantic species
Bibliographic record
Abstract
Herders are surface-collecting agents that can effectively reduce the surface area of oil slicks during a spill. Currently, two herding agents, Siltech OP-40 (OP-40) and ThickSlick 6535 (TS6535), are approved for use in oil spill response operations by the United States Environmental Protection Agency National Contingency Plan. These products may be deployed when there is evidence that environmental conditions are appropriate for their application and that their use will result in a net environmental benefit. Because the toxicity of these compounds is still poorly understood, toxicity of OP-40 and TS6535 was tested on four commercially relevant North Atlantic marine species: early life stages of green sea urchin (Strongylocentrotus droebachiensis), American lobster (Homarus americanus), Atlantic cod (Gadus morhua) and lumpfish (Cyclopterus lumpus). Lethal and sublethal toxicity data (LC50 and EC50) were determined at different time points. Siltech OP-40 was found to be between 4 and 78 times more toxic than TS6535. Toxicity values ranged from 1.0 (20-min EC50 in sea urchin fertilization) to 13.4 mg/L (3-hr LC50 in lumpfish) for OP-40, and from 7.6 (72-hr LC50 in 24-hour-old embryo cod) to 476.6 mg/L (24-hr EC50 in 20-day-old cod embryo) for TS6536. In terms of decision-making for oil spill response, data from this study supports their operational use, as the measured toxicity values exceeded the theoretical concentrations expected in the environment following the deployment of herding agents.
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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 | 0.000 | 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) | 0.001 | 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 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".