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Record W4309935885 · doi:10.31276/vjst.64(11).48-53

Ecological risks of some heavy metals in sediment samples collected from downstream of the Red river

2022· article· en· W4309935885 on OpenAlexaboutno aff
Thi Tham Trinh, Thi Trinh Le

Bibliographic record

VenueMinistry of Science and Technology Vietnam · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
Fundersnot available
KeywordsSedimentEnvironmental scienceHeavy metalsPollutionEnvironmental chemistryRiver ecosystemAquatic ecosystemEcosystemHydrology (agriculture)EcologyGeologyChemistryBiologyGeomorphology

Abstract

fetched live from OpenAlex

This study aimed to assess the accumulation of some heavy metals such as Cu, Pb, Cd, and Cr in the sediments collected from downstream of the Red river from the south of Hanoi city to Nam Truc district, Nam Dinh province. Besides, the geological accumulation index (Igeo) and the potential ecological risk index were calculated to understand the impact of heavy metal content in the sediments on the ecosystem. The results showed that the concentration of several metals (Cu, Pb, Cd, Cr) in 20 sediment samples was lower than the permitted values specified in Technical Regulations on sediment quality (QCVN 43:2017/BTNMT). However, according to the Canadian guidelines, the concentrations of metals in 50% of samples had a low level of effect. The potential ecological risk index of metals ranges from 1.8 to 11.6, revealing that the study area has a low-level metal risk. This data can clarify the area’s potential risk level and provide the scientific basis for recommending measures to control and reduce sources of metal pollution into the aquatic environment.

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 score0.016
Threshold uncertainty score0.032

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 head0.026
GPT teacher head0.262
Teacher spread0.236 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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