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Record W4389805378 · doi:10.1016/j.envint.2023.108388

Bioaccumulative chemicals are either too hard or too soft: Conceptual density functional theory as a screening tool for emerging pollutants

2023· article· en· W4389805378 on OpenAlexafffund
Xiaolei Li, James S. M. Anderson, Karl J. Jobst

Bibliographic record

VenueEnvironment International · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicChemistry and Chemical Engineering
Canadian institutionsMemorial University of Newfoundland
FundersDirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de MéxicoNatural Sciences and Engineering Research Council of CanadaUniversidad Nacional Autónoma de México
KeywordsPollutantBioaccumulationEnvironmental scienceEnvironmental chemistryEcologyChemistryBiology

Abstract

fetched live from OpenAlex

Conceptual density functional theory (CDFT) descriptors were computed to predict the environmental fate of ∼6,000 widely used industrial chemicals. CDFT descriptors aligned with a molecule’s possible bioaccumulation mechanism, i.e., soft chemicals are lipophilic, whereas hard chemicals may bioaccumulate by other mechanisms such as protein binding. The results have provided us with a new “rule of thumb” to guide risk assessment of chemical hazards: suspected persistent organic pollutants are either too hard (η>0.40 hartree) or too soft (α>200 Å3). This offers a novel approach to environmental risk assessment using two fundamental properties of a molecule.

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 categoriesInsufficient 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 score0.251
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

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)0.0170.001

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 head0.034
GPT teacher head0.253
Teacher spread0.219 · 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

Citations8
Published2023
Admission routes2
Has abstractyes

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