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Record W2063459352 · doi:10.1021/es0496524

Biotic Ligand Model, a Flexible Tool for Developing Site-Specific Water Quality Guidelines for Metals

2004· review· en· W2063459352 on OpenAlexaff
Chris M. Wood

Bibliographic record

VenueEnvironmental Science & Technology · 2004
Typereview
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBiotic Ligand ModelEnvironmental chemistryChemistryLigand (biochemistry)Abiotic componentDissolved organic carbonMetalBioavailabilityMetal toxicityCopperEcologyHeavy metalsBiochemistryBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

The biotic ligand model (BLM) is a mechanistic approach that greatly improves our ability to generate site-specific ambient water quality criteria (AWQC)for metals in the natural environment relative to conventional relationships based only on hardness. The model is flexible; all aspects of water chemistry that affect toxicity can be included, so the BLM integrates the concept of bioavailability into AWQC--in essence the computational equivalent of water effect ratio (WER) testing. The theory of the BLM evolved from the gill surface interaction model (GSIM) and the free ion activity model (FIAM). Using an equilibrium geochemical modeling framework, the BLM incorporates the competition of the free metal ion with other naturally occurring cations (e.g., Ca2+, Na+, Mg2-, H+), togetherwith complexation by abiotic ligands [e.g., DOM (dissolved organic matter), chloride, carbonates, sulfide] for binding with the biotic ligand, the site of toxic action on the organism. On the basis of fish gill research, the biotic ligands appear to be active ion uptake pathways (e.g., Na+ transporters for copper and silver, Ca2+ transporters for zinc, cadmium, lead, and cobalt), whose geochemical characteristics (affinity = log K, capacity = Bmax) can be quantified in short-term (3-24 h) in vivo gill binding tests. In general, the greater the toxicity of a particular metal, the higher the log K. The BLM quantitatively relates short-term binding to acute toxicity, with the LA50 (lethal accumulation) being predictive of the LC50 (generally 96 h for fish, 48 h for daphnids). We critically evaluate currently available BLMs for copper, silver, zinc, and nickel and gill binding approaches for cadmium, lead, and cobalt on which BLMs could be based. Most BLMs originate from tests with fish and have been recalibrated for more sensitive daphnids by adjustment of LA50 so as to fit the results of toxicity testing. Issues of concern include the arbitrary nature of LA50 adjustments; possible mechanistic differences between daphnids and fish that may alter log K values, particularly for hardness cations (Ca2+, Mg2+); assumption of fixed biotic ligand characteristics in the face of evidence that they may change in response to acclimation and diet; difficulties in dealing with DOM and incorporating its heterogeneity into the modeling framework; and the paucity of validation exercises on natural water data sets. Important needs include characterization of biotic ligand properties at the molecular level; development of in vitro BLMs, extension of the BLM approach to a wider range of organisms, to the estuarine and marine environment, and to deal with metal mixtures; and further development of BLM frameworks to predict chronic toxicity and thereby generate chronic AWQC.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0050.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0210.005

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 head0.125
GPT teacher head0.377
Teacher spread0.252 · 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 designTheoretical or conceptual
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

Citations664
Published2004
Admission routes1
Has abstractyes

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