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Record W2512256963 · doi:10.1016/j.emcon.2016.07.002

Environmental levels and toxicological potencies of a novel mixed halogenated carbazole

2016· article· en· W2512256963 on OpenAlexaffabout
Matthew Robson, Sri R. Chaudhuri, Nicole Riddell, Robert McCrindle, Brock Chittim, Robert Parette, Un-Ho Jin, Stephen Safe, David G. Poirier, Ralph Ruffolo, Richard D. Dyer, Rachael Fletcher, Paul A. Helm, Eric J. Reiner

Bibliographic record

VenueEmerging contaminants · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsUniversity of GuelphBrock UniversityCanadian Rheumatology AssociationUniversity of TorontoMinistry of Energy, Northern Development and MinesMinistry of the Environment, Conservation and Parks
Fundersnot available
KeywordsCarbazoleChemistryEnvironmental chemistryToxicologyOrganic chemistryBiology

Abstract

fetched live from OpenAlex

The present work involves an extensive analytical and toxicological description of a recently identified mixed halogenated carbazole found in sediment samples, 1,8-dibromo-3,6-dichloro-9H-carbazole (BCCZ). Concentrations and the relative effect potency (REP) were calculated for the target BCCZ in a set of stream sediments collected in 2008 in Ontario, Canada. The levels calculated for BCCZ as compared to those previously assessed for legacy persistent organic pollutants (POPs) in the same samples revealed a significant contribution of BCCZ to the total organic chemical contamination (<1%–95%; average 37%). The corresponding dioxin toxic equivalencies (TEQs) of BCCZ in the sediment extracts were estimated from experimental REP data. The experimental data presented supports the classification of this emerging halogenated chemical as a contaminant of emerging environmental concern. Although potential emission sources could not be identified, this study highlights the importance of on-going research for complete characterization of halogenated carbazoles and related compounds.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.999

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)0.0020.000

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 head0.019
GPT teacher head0.233
Teacher spread0.214 · 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

Citations21
Published2016
Admission routes2
Has abstractyes

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