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Record W3213957692 · doi:10.1002/etc.5247

A Critical Review of the Availability, Reliability, and Ecological Relevance of Arctic Species Toxicity Tests for Use in Environmental Risk Assessment

2021· review· en· W3213957692 on OpenAlexafffund
Rebecca R. Eldridge, Benjamin de Jourdan, Mark L. Hanson

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsUniversity of ManitobaHuntsman Marine Science Centre
FundersEnvironment and Climate Change CanadaPolar Knowledge CanadaUniversity of Manitoba
KeywordsArcticContext (archaeology)Risk assessmentEnvironmental scienceRelevance (law)EcologyReliability (semiconductor)BiologyComputer science

Abstract

fetched live from OpenAlex

There is a pressing need to understand the impact of contaminants on Arctic ecosystems; however, most toxicity tests are based on temperate species, and there are issues with reliability and relevance of bioassays in general. Together this may result in an underestimation of harm to Arctic organisms and contribute to significant uncertainty in risk assessments. To help address these concerns, a critical review to assess reported effects for these species, quantify methodological and endpoint relevance gaps, and identify future research needs for testing was performed. We developed uniform criteria to score each study, allowing an objective comparison across experiments to quantify their reliability and relevance. We scored a total of 48 individual studies, capturing 39 tested compounds, 73 unique Arctic test species, and 95 distinct endpoints published from 1975 to 2021. Our analysis shows that of 253 test substance and species combinations scored (i.e., a unique toxicity test), 207 (82%) failed to meet at least one critical study criterion that contributes to data reliability for use in risk assessment. Arctic-focused toxicity testing needs to ensure that exposures can be analytically confirmed, include environmentally realistic exposure scenarios, and report test methods more thoroughly. Significant data gaps were identified as related to standardized toxicity testing with Arctic species, diversity of compounds tested with these organisms, and the inclusion of ecologically relevant sublethal and chronic endpoints assessed in Arctic toxicity testing. Overall, there needs to be ongoing improvement in test conduction and reporting in the scientific literature to support effective risk assessments in an Arctic context. Environ Toxicol Chem 2022;41:46-72. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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)0.027
metaresearch head score (Gemma)0.076
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 score0.027
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.076
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0160.011
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.030
GPT teacher head0.301
Teacher spread0.271 · 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
Published2021
Admission routes2
Has abstractyes

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