Fate and Fathead Minnow Embryotoxicity of Weathering Crude Oil in a Pilot-Scale Spill Tank
Bibliographic record
Abstract
For several years now, the Natural Resources Canada research facility at CanmetENERGY Devon (AB, Canada) has been performing experiments in a pilot-scale spill tank using 1200 L of river water to examine the physical and chemical behaviors of various crude oil/water mixtures under varying water temperature regimes. Because oil toxicity can be modulated by weathering of the petroleum products, the present study aimed to assess changes in fish embryotoxicity to mixed sweet blend crude oil as it weathered at air and water temperatures of 14 °C and 15 °C, respectively, for 28 d. The physicochemical behavior of the oil was also monitored. Water samples were taken from the spill tank 5 times during the 28-d experiment on days 1, 6, 14, 21, and 28 and were used to perform toxicity exposures using fathead minnow embryos (Pimephales promelas). For each water sampling day, newly fertilized embryos were exposed to a serial dilution of the spill tank water, noncontaminated river water (used in the spill tank), and a reconstituted water laboratory control. Embryos were raised until hatching. Although mortality was not significantly altered by the oil contamination over the time period, malformation occurrence and severity showed concentration-dependent responses to all contaminated water collected. The results suggest that days 14, 21, and 28 were the most toxic time periods for the fish embryos, which corresponded to increasing concentrations of unidentified oxidized organic compounds detected by a quadropole-time-of-flight system. The present study highlights a novel area for oil research, which could help us to better understand the toxicity associated with oil weathering for aquatic species. Environ Toxicol Chem 2021;40:127-138. © 2020 Her Majesty the Queen in Right of Canada. Reproduced with the permission of the Minister of Natural Resources Canada.
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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".