The effects of a simulated spill of diluted bitumen on invertebrates in a boreal lake environment
Bibliographic record
Abstract
To bring bitumen from Canada's Oil Sands to market requires transportation over sensitive boreal environments via rail, truck, and pipeline. With proposed expansion of pipeline infrastructure, there is a need for whole-ecosystem research evaluating fate and toxicity of oil spills specific to freshwater environments; the Boreal Lake Oil Release Experiment by Additions to Limnocorrals (BOREAL) aimed to address this. The BOREAL study was conducted in an oligotrophic lake (Lake 260) at the IISD-Experimental Lakes Area in Summer 2018. Nine 10-metre diameter, ~ 100-m3, limnocorrals were deployed, with seven treated with different volumes of a diluted bitumen product in a regression design accompanied by two reference limnocorrals. Dilbit volumes ranged from 1.5 L to 180 L, which is representative of historical oil:water ratios for pipeline spills in North America between the 50th and 99th centile (2008-2018). Zooplankton, emerging insects, and benthic invertebrates were monitored pre- and post-spill for abundance and community composition. By 13 days post-spill, zooplankton abundance had decreased in all limnocorrals and did not recover to pre-treatment values, with rotifers becoming the dominant phylum. No discernable impact based on treatment to zooplankton community diversity was observed. No impact was observed to resident benthic invertebrate communities relative to control limnocorrals; however, a concentration-response decline was observed in total insect emergence. Emergence rate declines were confounded by benthic impacts and presence of submerged oil and will require further work to elucidate drivers of long-term impacts. The physical component of oil was observed to be the likely driver of pleuston (water striders) immobility and mortality.
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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".