Assessing the toxicity of chemically fractionated Hamilton Harbour (Lake Ontario) sediment using selected aquatic organisms
Bibliographic record
Abstract
Abstract Studies of the sediments of Hamilton Harbour, Lake Ontario, Canada, have shown variable degrees of pollution with a large number of organic and inorganic pollutants. Three areas in the Harbour – Windemere Basin, Cootes Paradise and Randle Reef – exhibited particularly high levels of contaminants, with concomitant impacts on benthic organisms. Sediment samples examined in this study were taken from a site in Randle Reef in Hamilton Harbour and a station (LE 23) in Lake Erie used as a reference sample. The samples were subjected to chemical fractionation to remove organic contaminants, with one fraction being used as total extract, and another aliquot being subjected to silica gel fractionation to give four fractions. Each fraction was chemically analysed and an aliquot used for bioassays following exchange with dimethylsulfoxide. Standard biotests were performed with Daphnia magna, Hyalella azteca, Pimephales promelas (fathead minnows) and Selenastrum capricornutum. Results from direct sediment contact bioassays indicated that sediment from Randle Reef is highly toxic, whereas the Lake Erie sample had no observable impacts. Total extract when added at 1% to the bioassays replicated the solid phase with acute toxicity for Randle Reef, and no effect on Lake Erie. For the silica gel fractionation, Fraction 1 (F1) showed similar toxicity as the total extract, even at low additions, whereas F2–4 gave variable and inconclusive results. F1 eluted with hexane contained the non‐polar fractions, predominantly the polyaromatic hydrocarbons, and these compounds are the most likely causative agents for the highly acute toxicity observed in the sediment of Randle Reef.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".