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Distribution of heavy metals in sediment along the Southern coast of Vietnam

2020· article· en· W3109827930 on OpenAlexaboutno aff
Nguyễn Phúc Cẩm Tú, Nguyễn Ngọc Hà, Nguyen Nhu Tri, Nguyễn Văn Đông

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
Fundersnot available
KeywordsSedimentEnvironmental chemistryHeavy metalsCockleBiotaEnvironmental scienceAnimal scienceChemistryGeologyEcologyBiology

Abstract

fetched live from OpenAlex

Abstract The heavy metals (HM), particularly As, Cd, Pb and Hg, are considered most toxic to biota and environment. In this study, spatial and seasonal distribution of HMs (Cd, Pb, Hg and As) were measured in two sediment fractions (< 63 μm and 63 – 500 μm) collected in the farming area of blood cockle. A total of 104 sediment sampled along the Southern coast of Vietnam between December 2012 and July 2015 were examined. The average concentrations (μg/g) of As, Cd, Pb and Hg in sediment fraction of 63 – 500 μm ranged from 4.16 to 16.8, < 0.004 to 0.219, 9.52 to 17.3 and 0.031 to 0.076, respectively. While, the mean levels (μg/g) of As, Cd, Pb and Hg in sediment fraction of < 63 μm ranged from 4.59 to 12.8, < 0.004 to 0.187, 9.94 to 14.6 and 0.042 to 0.080, respectively. Generally, no statistically significant differences were found for concentrations of HMs in both fractions between two seasons and among provinces. The concentrations of HMs analyzed in sediment were compared to quality guidelines for the protection of aquatic life recommended by the Canadian Council of Ministers of the Environment (CCME) and the Vietnamese organizations (QCVN 43 : 2012/BTNMT). HM levels in all samples were lower than the Vietnamese regulation and the probable effect level in the CCME guideline. However, As levels in 67/103 and 84/104 of two fractions of < 63 μm and 63 – 500 μm, respectively, exceeded the threshold effect level of 7.24 μg/g in the CCME standard. It suggested that As accumulated in sediment in these provinces could be harmful to the aquatic organism.

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 score0.060
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.210
Teacher spread0.194 · 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".

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Citations4
Published2020
Admission routes1
Has abstractyes

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