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Record W4407914019 · doi:10.1093/inteam/vjaf033

Bioavailability and risk assessment of metals in freshwaters: is global regulatory implementation keeping pace with scientific developments?

2025· article· en· W4407914019 on OpenAlexaboutno aff
Graham Merrington, Robert W. Gensemer, Guy Gilron, Iain Wilson, Adam Peters, Rick van Dam, Lisa A. Golding, Jennifer L. Stauber, Jennifer Gadd, David K. DeForest, Emily Garman, Ellizabeth Middleton, Adam C. Ryan, Christopher A. Cooper, Erin Smith, Stijn Baken

Bibliographic record

VenueIntegrated Environmental Assessment and Management · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
Fundersnot available
KeywordsBioavailabilityRegulatory sciencePaceRisk analysis (engineering)Quality (philosophy)Aquatic ecosystemEnvironmental planningEnvironmental resource managementEnvironmental scienceBusinessComputer scienceBiochemical engineeringEnvironmental chemistryEngineeringEcologyChemistryBiologyGeography

Abstract

fetched live from OpenAlex

The scientific knowledge that enables the prediction of potential aquatic ecological risks due to exposure of metals based on freshwater chemistry data has been available for several decades. As a result, ecosystems can be protected using frameworks and procedures incorporated into regulatory approaches. Yet when evaluating how freshwater risks from metals are assessed globally, it is apparent that regulatory jurisdictions differ in their progress and approaches when accounting for bioavailability. It is entirely reasonable and appropriate for a lag in time between the development of the science and its incorporation into routine regulatory environmental protection. We openly acknowledge that this is not just a regulatory challenge and take a more holistic view of the implementation of the science that informs metal bioavailability. Implementation comprises the steps required to utilize science and knowledge to enable its practical, beneficial, and routine application in regulatory decision-making. Different regulatory jurisdictions have taken varied approaches to account for metal bioavailability. We have made specific use of frameworks that utilize limit values, such as water quality guidelines, criteria, and quality standards, to illustrate the similarities and differences in the implementation of bioavailability. Approaches taken in Europe, Canada, Australia and New Zealand, and the United States were reviewed and evaluated. Although some of these approaches or parts thereof have been successful, other aspects have been less so. In this evaluation, we have identified key commonly encountered obstacles and challenges in these approaches to the implementation of metal bioavailability. Finally, we provide an evidence-driven "road map" to the successful regulatory implementation of metal bioavailability in risk assessment drawn from successful components of the approaches reviewed. The application of this framework will enable regulatory jurisdictions to readily keep pace with the science pertaining to metal bioavailability and avoid the challenges experienced by others.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.285
Teacher spread0.278 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2025
Admission routes1
Has abstractyes

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