Aquatic ecotoxicology: what has been accomplished and what lies ahead? An Eastern Canada historical perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Our recent history shows that degradation of aquatic ecosystems essentially stems from industrialization, urbanization and increasing human populations. After a first industrial boom in the late 19th century, contamination pressures on receiving waters now appear to be continual because of expanding economies and technologies developing at the planetary scale. Given the diversity of issues, problems and challenges facing water quality today because of complex waste and chemical discharges into waterways, aquatic ecotoxicology has blossomed with time into a more mature discipline of the environmental sciences. Its two fundamental pillars, bioassays and biomarkers, have become essential tools that allow the determination of numerous and versatile effects measurements. Herein, we demonstrate some of the ways in which these<br />tools have been applied and how they have evolved over the past decades to appraise the ecotoxicity of contaminants impacting aquatic systems. Examples discussed are largely reflective of work conducted in the Environment Canada (EC) laboratories (Saint-Lawrence Centre, Montr&eacute;al, Canada). Success stories include improvement of industrial effluent quality contributing to beluga whale population recovery in the Saint-Lawrence River, biomarker field studies conducted with endemic and caged bivalves to more fully comprehend urban effluent adverse effects, and increased discernment on the hazard potential posed by emerging classes of chemicals. Ecotoxicology continues to be confronted with diverse issues and needs related to a myriad of chemical contaminants released to aquatic environments worldwide. To cope with these, ecotoxicology will have to bank on new tools (<em>e.g.</em>, toxicogenomics, bio-informatics, modeling)<br />and become more interdisciplinary by taking into account knowledge provided by other disciplines (<em>e.g.</em>, ecology, chemistry, climatology, microbiology) in order to more fully understand and adequately interpret hazard. This will be paramount to supply regulators and legislators with the sound and scientifically valid information needed in order to mitigate environmental degradation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it