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Record W4381715346 · doi:10.1039/d3em00070b

A framework for understanding the bioconcentration of surfactants in fish

2023· article· en· W4381715346 on OpenAlex
Michael S. McLachlan, Andrea Ebert, James M. Armitage, Jon A. Arnot, Steven T. J. Droge

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironmental Science Processes & Impacts · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Chemistry and Analysis
Canadian institutionsARC Resources (Canada)The Scarborough HospitalUniversity of TorontoASL Environmental Sciences (Canada)
FundersEuropean Chemical Industry Council
KeywordsBioconcentrationFish <Actinopterygii>Environmental chemistryPartition coefficientFraction (chemistry)Distribution (mathematics)Function (biology)ChemistryFisheryChromatographyBiologyMathematicsBioaccumulation

Abstract

fetched live from OpenAlex

measurements of anionic, cationic and nonionic surfactants in fish. In doing so, we demonstrate how the framework can be used to explore expected differences in bioconcentration behavior within a given sub-class of surfactants, to assess how pH will influence bioconcentration, to identify the underlying processes governing bioconcentration of a particular surfactant, and to discover knowledge gaps that require further research. This framework for amphiphilic chemicals may function as a template for improved understanding of the accumulation potential of other ionizable chemicals of environmental concern, such as pharmaceuticals or dyes.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.280
Teacher spread0.249 · 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