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Record W3021200102 · doi:10.20886/jklh.2020.14.1.43-52

KANDUNGAN MERKURI DALAM BEBERAPA MEDIA SEKITAR PENAMBANGAN EMAS SKALA KECIL (PESK) DI KALIMANTAN TENGAH

2020· article· id· W3021200102 on OpenAlexaboutno aff
Alfrida Ester Suoth, Sri Unon Purwati, Siti Masitoh, Alfonsus H Hariandja, Edy Junaidy

Bibliographic record

VenueJurnal Ecolab · 2020
Typearticle
Languageid
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMercury (programming language)Water qualityEnvironmental scienceNational standardQuality standardMercury contaminationSedimentContaminationEnvironmental chemistryFisheryChemistryEcologyBiology

Abstract

fetched live from OpenAlex

Research on mercury (Hg) contamination in environmental media around ASGM activities is still required, as a database for the formulation of mercury phasing-out and reduction plans.This paper presents the results of research on the distribution of mercury concentrations in river waters, freshwater fish, and sediments as the impact of ASGM activities in Central Kalimantan.The data used are data set from P3KLL measurements in 1999-2008 and the latest measurement results conducted by the PB3-KLHK Directorate in 2018.Mercury analysis was performed using Mercury Analyzer Hg-5000 cold vapor method and the preparation of test samples in accordance with Standards Japan International (JIS) and Indonesian National Quality Standard (SNI).The results indicate that in most sampling locations, the concentration of mercury in river water was still below the quality standard of class I water on the Government Regulation Number 82 Year 2001 (0,001 mg/L).Still, the value at two locations was higher than the quality standard.Mercury contained in freshwater fish samples from rivers around ASGM was ranging between 0,08 and 0,224 mg/kg.This value is still below the value of metal contamination requirements in fish, according to SNI:7387 2009 (0,5 mg/kg).Mercury content in the sediment is ranging between 0,0291 to 0,45 mg/kg, wherein several locations are above the standard in the Quality Guidelines for Freshwater of Canadian Environmental Quality (CEQ), which is 0,17 mg/kg.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.005

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 head0.027
GPT teacher head0.244
Teacher spread0.217 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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