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Record W2107212109 · doi:10.4491/ksee.2015.37.3.191

Estimation of Contamination Level of Sediments Obtained from the Outport of Jeju Harbor

2015· article· en· W2107212109 on OpenAlexaboutno aff
Sangmin Lee, Dongsoo Kim, Taeyoon Lee

Bibliographic record

VenueJournal of Korean Society of Environmental Engineers · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
Fundersnot available
KeywordsContaminationEnvironmental scienceEstimationSedimentEnvironmental chemistryHydrology (agriculture)GeologyEcologyBiologyEngineeringChemistryGeotechnical engineeringGeomorphology

Abstract

fetched live from OpenAlex

In this study, physico-chemical properties and heavy metal contents of sediment samples were determined to characterize the current pollution levels of the sediments.Ignition loss of the samples obtained from outside of the harbor was relatively lower than that from the samples obtained inside of the harbor.Heavy metal pollution was not serious except Ni.Concentrations of Ni for J1, J3, and J4 exceeded 16 mg/kg.Thus, these areas were classified as lowest effect level according to Ontario sediment quality guidelines.Evaluation of sediments pollution using Igeo and R resulted as non-pollution for all considered metals, which indicated that no outer pollutants entered in the Jeju outport harbor.However, drastic increase of Cu concentrations was observed.Its concentration obviously increased toward the inside of the outport harbor.Therefore, careful attention and plan for the protection and remediation of sediments is required to maintain the cleanness of the Jeju outport harbor.

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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.032
GPT teacher head0.239
Teacher spread0.207 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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