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Record W199692512

Factors Affecting Critical Toxicokinetic Parameters of Polychlorinated Biphenyls (PCBS) in Japanese Koi (CYPRINUS CARPIO): Effect of Diet on Chemical Assimilation and Influence of Feces to Whole Body Chemical Elimination

2009· article· en· W199692512 on OpenAlexfundno aff
Jian Liu

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Windsor
KeywordsBioaccumulationCyprinusAssimilation (phonology)Environmental chemistryToxicokineticsCarpChemistryFecesPolychlorinated biphenylToxicologyEnvironmental scienceBiologyFish <Actinopterygii>FisheryEcologyBiochemistryMetabolism
DOInot available

Abstract

fetched live from OpenAlex

This thesis provides enhanced calibration of critical parameters, chemical uptake efficiency (AE), chemical whole body elimination rate coefficient (ktot), and fecal elimination rate coefficients (kex), which are applied in a generalized fish bioaccumulation model applicable to polychlorinated biphenyls. Chapter 2 presents measurements of chemical AE based on a mass balance method and shows that both chemical hydrophobicity and diet properties have a significant influence on the chemical AE. Lipid content in the diet was not shown to have significant effect on the chemical AE. Chapter 3 provides measurements of ktot and kex for both labile and recalcitrant PCB congeners across three dose levels. First order kinetics was confirmed in the study, which also showed that fecal elimination counted for only a small fiction of the whole body elimination. Gill elimination and metabolic biotransformation were shown to be equally important as elimination routes for labile congeners.

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)0.001
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueScholarship at UWindsor (University of Windsor)Same topicToxic Organic Pollutants ImpactFrench-language works237,207