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Record W4290488795 · doi:10.11648/j.ajep.20221101.12

Study of Cyanide Contamination of Market Garden and Agricultural Products Grown Around the Samira Gold Mine (Niger)

2022· article· en· W4290488795 on OpenAlexaboutno aff
Hassane Adamou Hassane, Abdoulkadri Ayouba Mahamane, Rabani Adamou

Bibliographic record

VenueAmerican Journal of Environmental Protection · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCassava research and cyanide
Canadian institutionsnot available
Fundersnot available
KeywordsCyanideTailingsSoil waterGold miningContaminationEnvironmental chemistryEnvironmental sciencePollutionAgricultureMining engineeringChemistryGeologyEcologySoil scienceBiology

Abstract

fetched live from OpenAlex

The term cyanide refers to all the compounds producing the ─C≡N group. It comes from both anthropogenic and natural origins. Its presence in the environment is largely related to gold mining. Cyanide is very scary because of its toxicity causing very deadly environmental consequences. The objective of this work is to study the fate of cyanide and assess its contamination on the environment in the vicinity of a potential source of pollution such as a gold mine. In this study, soils and foods samples from the Samira gold mine and its surroundings in southwestern Niger were collected, analysed and compared with equivalent control samples grown in areas free of any industrial cyanide source. Total cyanide contents in the soils of the Samira site and its surroundings are 2 to 104 times higher than the Canadian standard (0.90 µg g-1 CN-) for agricultural soils, while the control soils are almost free of cyanide. These results show a migration of cyanide from the mine tailings to the surrounding area and these soils are unsuitable for any crop. The produced foods on these polluted soils have total cyanide contents 2 to 5 times higher than their controls. These contaminated matrices reveal negative impacts of the Samira mine's gold activities on its immediate environment. Ingestion of these foods would lead to serious health consequences for local populations.

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 score0.007
Threshold uncertainty score0.014

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 head0.012
GPT teacher head0.200
Teacher spread0.187 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Environmental ProtectionSame topicCassava research and cyanideFrench-language works237,207