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Record W2119937795 · doi:10.4319/lo.2002.47.2.0505

Influence of temperature on Cd accumulation by species of the biomonitor <i>Chaoborus</i>

2002· article· en· W2119937795 on OpenAlexaff
Marie‐Noéle Croteau, Landis Hare, André Tessier

Bibliographic record

VenueLimnology and Oceanography · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsBioaccumulationLarvaCadmiumBiologyMidgeGrowth rateFood chainEnvironmental chemistryEcologyZoologyChemistry

Abstract

fetched live from OpenAlex

We exposed larvae of several species of the phantom midge Chaoborus to the trace metal cadmium (Cd) to determine whether Cd accumulation rates varied with ambient temperature. Because this predator is known to accumulate its Cd mainly from food rather than from water, we presented the Cd in food, that is, Cd‐rich copepods taken from a lake near a metal smelter. Rates of Cd accumulation by larvae of Chaoborus americanus, C. flavicans, and C. punctipennis were measured at three temperatures (5, 14, and 228C) covering the seasonal range encountered by these animals. The rates at which all species accumulated Cd increased with temperature. To explain these results, we fit our experimental data to a bioaccumulation model that allowed us to estimate Cd assimilation efficiency, Cd‐efflux rate, and larval growth rate. Temperature‐related changes in Cd accumulation rates were best explained by changes in the rate at which Chaoborus larvae ingested prey as well as the efficiency with which they assimilated Cd from their food. Neither the rate of larval growth nor the rate at which larvae lost Cd was influenced by temperature. Extrapolations of our laboratory results to the field suggest that our model results provide a realistic representation of the processes involved in Cd accumulation by larvae of this common aquatic insect.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.210
Teacher spread0.200 · 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 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

Citations30
Published2002
Admission routes1
Has abstractyes

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