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Record W2113829939 · doi:10.1002/etc.5620190920

Physiological effects of chronic copper exposure to rainbow trout (<i>Oncorhynchus mykiss</i>) in hard and soft water: Evaluation of chronic indicators

2000· article· en· W2113829939 on OpenAlexaff
Lisa N. Taylor, James C. McGeer, Chris M. Wood, D. G. McDonald

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSoft waterRainbow troutGillCopperAcclimatizationBiotic Ligand ModelBioconcentrationAnimal scienceToxicityMetalHard waterTroutBioaccumulationMetal toxicityChemistryElectrolyteJuvenileEnvironmental chemistryChronic toxicityToxicologyFish <Actinopterygii>BiologyFisheryHeavy metalsEcology

Abstract

fetched live from OpenAlex

Abstract Effects of chronic copper exposure on a suite of indicators were examined: acute toxicity, acclimation, growth, sprint performance, whole-body electrolytes, tissue residues, and gill copper binding characteristics. Juvenile rainbow trout were exposed for 30 d to waterborne copper in hard water (hardness = 120 mg/L as CaCO3, pH = 8.0, Cu = 20 and 60 μg/L) and soft water (hardness = 20 mg/L as CaCO3, pH = 7.2, Cu = 1 and 2 μg/L). Significant acclimation to the metal occurred only in fish exposed to 60 μg/L, as seen by an approx. twofold increase in 96-h LC50 (153 vs 91 μg Cu/L). Chronic copper exposure had little or no effect on survival, growth, or swimming performance in either water hardness, nor was there any initial whole-body electrolyte loss (Na+ and Cl−). The present data suggest that the availability of food (3% wet body weight/day, distributed as three 1% meals) prevented growth inhibition and initial ion losses that usually result from Cu exposure. Elevated metal burdens in the gills and livers of exposed fish were measures of chronic copper exposure but not of effect. Initial gill binding experiments revealed the necessity of using radiolabeled Cu (64Cu) to detect newly accumulated Cu against gill background levels. Using this method, we verified the presence of saturable Cu-binding sites in the gills of juvenile rainbow trout and were able to make estimates of copper-binding affinity (log Kgill=Cu) and capacity (Bmax). Furthermore, we showed that both chronic exposure to Cu and to low water calcium had important effects on the Cu-binding characteristics of the gills.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0130.000

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 head0.006
GPT teacher head0.214
Teacher spread0.208 · 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 designBench or experimental
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

Citations146
Published2000
Admission routes1
Has abstractyes

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