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Record W3169321240 · doi:10.3934/environsci.2021012

Persistent and carcinogenic polycyclic aromatic hydrocarbons in the north-western coastal marine environment of India

2021· article· en· W3169321240 on OpenAlexaboutno aff
Pravin U. Singare, J. P. Shirodkar

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsnot available
Fundersnot available
KeywordsPolycyclic aromatic hydrocarbonEnvironmental chemistryEnvironmental scienceOil spillCarcinogenGeographyEnvironmental protectionChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The carcinogenic and endocrine-disrupting PAHs were investigated in surface water of the north-western creeks of India. The concentrations of ΣPAHs were found to vary in the range of 114.32-347.04 μg L-1, (mean 224.78 ± 8.85 μg L-1), out of which 49.12% contribution is due to ΣC-PAHs. The assessment of toxicity and biological risk arising due to individual C-PAHs was made by calculating their toxic equivalent quantity. The level of individual C-PAHs was reported exceeding the final chronic values, Canadian water quality guideline values and Netherlands maximum permissible concentration values set for the protection of aquatic life. The mean BaP concentration (10.32 ± 2.75 μg L-1) was above the European Directive 2008/105/EC Environmental Quality Standards (EQS) value; while the sum of BkF + BbF (26.76 μg L-1) and BghiP + InP (19.59 μg L-1) were significantly higher than that set by the EQS. The results of the present study will help in understanding the global distribution and fate of PAHs which is required for implementing the necessary steps towards mitigation of the ecotoxicological risk arising due to the existence of such contaminants in the aquatic environment across the world.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.087
GPT teacher head0.407
Teacher spread0.320 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)→Same topicToxic Organic Pollutants Impact→French-language works237,207→