Deleterious Properties Retained By Diesel Fuel Spilled In Northern Canada In Winter
Bibliographic record
Abstract
In March 1983, a fuel truck overturned at a bridge crossing the Cameron River, near Yellowknife, Northwest Territories, Canada, and spilled a quantity of diesel fiel. The spilled diesel fuel penetrated the snow cover, moved along the frozen surface of the ground and entered the ice-covered Cameron River. A sample of diesel fuel was recovered tlom beneath the river ice eight days after the initial spill. This sample from the river was compared with that from the original cargo in the truck in three quantitative and independent ways, namely gas chromatography with a comparison of the sample patterns by principal component analysis, acute toxicity to fish, and tendency to taint fish with an oily taste. The two samples were essentially the same in all respects, except for some subtle but consistent differences in the relative proportions of some individual hydrocarbons. The river samples were shown to contain slightly higher proportions of the Cs to Cq alkane components. Slightly lower proportions of alkanes eluted after CU, possibly as a result of losses due to sediment adsorption or fractionation under the ice. Evidently the low ambient temperatures and cover by ice and snow reduced greatly the ‘weathering’ phenomenon often described with spilled oils, and permitted the oil to retain its toxic and tainting properties.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 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".