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Record W2000347898 · doi:10.4081/xeno.2013.e8

Aquatic ecotoxicology: what has been accomplished and what lies ahead? An Eastern Canada historical perspective

2013· article· en· W2000347898 on OpenAlexafffundabout
C. Blaise, François Gagné

Bibliographic record

VenueJournal of Xenobiotics · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsEnvironment and Climate Change Canada
FundersHealth CanadaScience and Technology Directorate
KeywordsEcotoxicologyAquatic ecosystemPopulationEnvironmental planningEnvironmental scienceEnvironmental protectionEcologyBiologySociology

Abstract

fetched live from OpenAlex

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 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, Montréal, 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 (e.g., toxicogenomics, bio-informatics, modeling) and become more interdisciplinary by taking into account knowledge provided by other disciplines (e.g., 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.095
Threshold uncertainty score0.689

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.009
Science and technology studies0.0090.008
Scholarly communication0.0100.004
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.018
GPT teacher head0.223
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations6
Published2013
Admission routes3
Has abstractyes

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