MétaCan
Menu
Back to cohort
Record W2948284773

Mercury and Heavy Metal Origin and Contamination of the Puyango-Tumbes River System, Ecuador

2015· article· en· W2948284773 on OpenAlexaboutno aff
Robert J. Kaplan, Marcello M. Veiga, Carolina Gonzalez-Mueller, Colon Velasquez-Lopez, L. N. Granda, Leonaor Leonor Rivera

Bibliographic record

Venue2015-Sustainable Industrial Processing Summit · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMercury (programming language)TailingsGold miningEnvironmental scienceEnvironmental chemistryContaminationSoil waterCadmiumSedimentTonneMining engineeringChemistryGeologySoil science
DOInot available

Abstract

fetched live from OpenAlex

Worldwide Artisanal Gold Miners (AGM) use significant amounts of mercury, accounting for more than 30% of all industrial uses. UNEP (2013) estimates that AGM is emitting and releasing 1400 tonnes/a of mercury. Processing centres were established in the 1990s in Portovelo, Ecuador to provide miners with gold extraction services. Miners amalgamate a portion of the gold, but centre owners retain the residual Hg-contaminated tailings using cyanidation to recover the remaining 60 - 80% of the gold. Based on surveys of 52 out of 87 centres, 1.1-1.85 tonnes of metallic mercury contained in over 880,000 tonnes of tailings are discharged into the Puyango-Tumbes River annually. This mercury represents a loss of approximately 14% of the total mercury used by AGM/a in the region. An additional 19% of the mercury is lost when amalgam is evaporated. An average of 5.7 tonnes of cyanide per month (a total of over 4,500 tonnes/a) is consumed by approximately 68 centres. In total, 39 river-bank sediments and 31 soils were sampled. Mercury contamination in sediment exceeded the CCME TEL - Canadian Council of Ministers of the Environment threshold effect level in 23 sites. The highest level detected was 30.79 mg/kg in sediment; all soil samples were below 2 mg/kg. An abandoned tailings pit recorded a mercury level of 744.2 mg/kg. Elevated mercury levels in sediment were detected 160 km distant from source, demonstrating that AGM-discharged mercury can flow long distances attached to particulate matter. Arsenic, Cadmium, Copper, Lead and Zinc levels in water, sediment and soil samples were also found to be above safe standards at many sites. In sediments, Arsenic levels were exceeded at 31 sites, the highest recorded was 12,580 mg/kg; Cadmium – 8 sites ( A total of 25 fish samples were taken from 3 sites in the river system 45 to 93 km from the source. Dorado fish recorded mercury levels ranging from 0.02 to 0.99 mg/kg; Aquila fish (a bottom feeder) had levels from 0.18 to 0.98 mg/kg. KEYWORDS: Ecuador, Puyango-Tumbes, mercury, ASGM, AGM, miners, mining, heavy metals, cyanide, water, sediments

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 score0.525
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.037
GPT teacher head0.271
Teacher spread0.234 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venue2015-Sustainable Industrial Processing SummitSame topicMercury impact and mitigation studiesFrench-language works237,207