MétaCan
Menu
Back to cohort

Arsenic Contamination of Soils in the Vicinity of Abandoned Seongan Mine

2005· article· en· W1965884149 on OpenAlexaboutno aff
Sehyun Kim, Wongyu Choi

Bibliographic record

VenueGeosystem Engineering · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoal and Its By-products
Canadian institutionsnot available
Fundersnot available
KeywordsTailingsContaminationEnvironmental scienceArsenicSoil waterMining engineeringEnvironmental chemistrySoil contaminationEnvironmental engineeringWaste managementGeologyChemistrySoil scienceEngineering

Abstract

fetched live from OpenAlex

The heavy metal concentration analysis of soils was performed to study arsenic contamination around abandoned Seongan metal mine where mine tailings is estimated approximately 42,000 m3. It is resulted that total As concentrations of top soil and tailings at the dumping site were 736± 1,223 mg/kg and 911±453 mg/kg, respectively. These values relatively higher than EU and Canadian standards for industrial region. And soluble As concentrations of those the dumping site were 387±411 mg/kg and 146±109 mg/kg, respectively, that exceeded Korean apprehension and counterplan standards. And, As contamination of soils was partially identified adjacent to the dressing plant and along the down stream from the mine, while contamination by the other heavy metals was found to be insignificant. In this specific case, recycling of the removable tailings can be considered to take advantage of its large amount, site accessibility and substantial demand for adjacent cement manufacturing factories.

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 score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.009
GPT teacher head0.172
Teacher spread0.163 · 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

Citations1
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueGeosystem EngineeringSame topicCoal and Its By-productsFrench-language works237,207