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Record W2897856296 · doi:10.21315/jps2018.29.s3.10

Heavy Metal Concentrations in Tin Mine Effluents in Kepayang River, Perak, Malaysia

2018· article· en· W2897856296 on OpenAlexaboutno aff
Farhana Ahmad Affandi, Mohd Yusoff Ishak

Bibliographic record

VenueJournal of Physical Science · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
FundersUniversiti Putra Malaysia
KeywordsArsenicBariumTinCadmiumEffluentEnvironmental chemistryManganeseZincInductively coupled plasma mass spectrometryChristian ministryCobaltChromiumTailingsMetallurgyEnvironmental scienceSedimentCassiteriteMetalChemistryMaterials scienceEnvironmental engineeringMass spectrometryGeology

Abstract

fetched live from OpenAlex

A preliminary study on physico-chemical properties and heavy metal concentrations, i.e., aluminium (Al), arsenic (As), barium (Ba), cadmium (Cd), cobalt (Co), copper (Cu), chromium (Cr), iron (Fe), manganese (Mn), nickel (Ni), lead (Pb), selenium (Se) and zinc (Zn), was conducted at the nearest point of tin mine effluents in Kepayang River, Perak, Malaysia. Composite samples of surface water and sediments were analysed using inductively coupled plasma mass spectrometry (ICP-MS) and data were compared with the Malaysia's Ministry of Health (MOH) and the Canadian Council of Ministers of the Environment (CCME) guidelines. The concentrations of As and Fe in both water and sediment were found to have exceeded the MOH and CCME guidelines. The output from this study can present as a background report on metal concentrations of tin mine effluents, which will be useful for future monitoring works.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.276
Teacher spread0.265 · 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

Citations14
Published2018
Admission routes1
Has abstractyes

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