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Record W2468936159

부산 남항 퇴적물의 오염도 평가 연구

2013· article· ko· W2468936159 on OpenAlexaboutno aff
이태윤

Bibliographic record

Venue한국폐기물자원순환학회지 · 2013
Typearticle
Languageko
FieldAgricultural and Biological Sciences
TopicAgriculture, Soil, Plant Science
Canadian institutionsnot available
Fundersnot available
KeywordsDredgingSedimentEnvironmental scienceEnvironmental chemistryContaminationLoss on ignitionHeavy metalsPollutionGeologyChemistryOceanography
DOInot available

Abstract

fetched live from OpenAlex

Sediments samples were collected at Busan South harbor where dredging has been initiated since 2010 to clean up the bottom of harbor. In this study, we tried to determine physico-chemical properties and heavy metal contents of sediments for the purpose of deciding contamination levels of the sediments. From the total organic carbon, XRD, and XRF analyses, all samples showed similar elements, oxides, and minerals. In general, moderately high concentrations of Cu, Pb, and Zn were found in the samples. Heavy metal contents of sediments were compared with USEPA sediment quality standards and ontario sediment quality guidelines. Ignition losses of the samples were greater than 8%, which is a value indicating whether the sample is heavily polluted or moderately polluted. All the samples were classified as heavily polluted. Therefore, sediments obtained from dredging should be carefully treated to avoid other adverse environmental effects.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.019

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 head0.015
GPT teacher head0.193
Teacher spread0.178 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venue한국폐기물자원순환학회지Same topicAgriculture, Soil, Plant ScienceFrench-language works237,207