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Record W2793318910 · doi:10.11159/ijepr.2018.003

A Comparison of Antimony in Natural Water with Leaching Concentration from Polyethylene Terephthalate (PET) Bottles

2018· article· en· W2793318910 on OpenAlexvenueno aff
Mihyun Jo, Taeyuel Kim, Sirim Choi, Jongpil Jung, Hee-il Song, Hyunjin Lee, Gyoungsu Park, Jo-Gyo Oh, Jai-Young Lee

Bibliographic record

VenueInternational Journal of Environmental Pollution and Remediation · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsnot available
Fundersnot available
KeywordsPolyethylene terephthalateAntimonyLeaching (pedology)PolyethyleneNatural mineralMaterials sciencePulp and paper industryChemistryEnvironmental scienceComposite materialMineralogyMetallurgySoil science

Abstract

fetched live from OpenAlex

is one of the trace hazardous compounds in drinking water. We investigated Sb concentration on natural environment such as river, reservoir, groundwater and raw water for bottled water. The natural content of Sb in northern Gyeonggi province in South Korea showed range from 0.00~1.64 g/L. The average of Sb in 47 brands of bottled water was 0.57 g/L on market. As a results of leaching experiment, was leached from polyethylene terephthalate(PET) bottles under storage condition at 35, 45 and 60. Sb concentration was increased from 1.04 to 9.84 g/L under 60 after 12weeks. UV-ray irradiation to bottled water not significantly induced antimony leaching for 14days.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.006
GPT teacher head0.248
Teacher spread0.242 · 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 teacher head, 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
Published2018
Admission routes1
Has abstractyes

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