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Record W2022593198 · doi:10.1109/icecc.2011.6067964

Contamination and potential toxicity of heavy metals in sediment of the ocean disposal site

2011· article· en· W2022593198 on OpenAlexfundno aff
Cheng‐Di Dong, Chiu Wen Chen, Chiu‐Wen Chen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
FundersNational Research Council CanadaNational Oceanic and Atmospheric Administration
KeywordsSedimentEnvironmental scienceEnvironmental chemistryContaminationPollutionHeavy metalsOrganic matterWater qualityEnrichment factorEnvironmental engineeringGeologyChemistry

Abstract

fetched live from OpenAlex

This study investigates the distribution, and accumulation of heavy metals in sediments of ocean disposal site. Sediment samples which collected from eleven locations in the ocean disposal site pre quarterly in 2009 were analyzed for metal content (e.g., Hg, Pb, Cd, Cr, Cu, Zn, Ni and Al), organic matter, and grain size. Base on the research results, the metal concentrations varied from 0.11 mg/kg for Cd to 198 mg/kg for Zn. All heavy metal concentrations excluding Hg and Ni of dumping area center in ocean disposal site is higher than other sites. Referring to enrichment factor (EF) assessment, both Cu and Cr in sediments of disposal area showed minor enrichment (EF <3) when comparing with the reference point which is located at outside of disposal site. Moreover, referring to sediment quality guidelines (SQGs), and mean ERM quotient (m-ERM-q), the dredged sediment disposal site is classified as “Medium — low contamination levels” where most samples (97%) have a medium — low (30%) probability of toxicity pollution.

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 score0.006
Threshold uncertainty score0.011

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 studies0.0000.000
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 head0.011
GPT teacher head0.204
Teacher spread0.193 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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