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Record W4318767807 · doi:10.1080/15275922.2023.2172478

Environmental Risk Assessment, Principal Component Analysis, Tracking the Source of Toxic Heavy Metals of Solid Gold Mine Waste Tailings, South Africa

2023· article· en· W4318767807 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnvironmental Forensics · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
Fundersnot available
KeywordsTailingsArsenicContaminationEnrichment factorPollutionEnvironmental scienceMunicipal solid wasteHeavy metalsEnvironmental chemistryGold miningMining engineeringPrincipal component analysisEnvironmental engineeringGeologyChemistryMetallurgyWaste managementMaterials science

Abstract

fetched live from OpenAlex

This study collected 21 soil samples from 30 to 120 cm depth, from 9 solid gold mine waste dumps in the Witwatersrand basin, South Africa. The samples were analysed using ICP-OES method to determine the concentrations of heavy metals. Principal component analysis (PCA) was performed to track sources of heavy metals, migration passages, their distributions and spatial variations at the study sites. The results of this study showed that the soil screening values (mg/kg) ranged from 2.20–7,070.00 Pb, 0.20–11.00 As, 0.06–2,630.00 Hg, 1.00–69.00 U, 0.02 − 4.20 Cd, and exceeded the background concentrations of the continental crust. The study results further showed that the average concentrations (mg/kg) of Pb (432.08), U (13.75), Tl (4.41), Ag (1.07), Cd (0.34) were highest at Durban Deep. Arsenic (59.86) and Sn (2.03) were highest at Krugersdorp, Kagiso, New Canada, and Shaft 17. The average values of Hg (625.56 µg/kg) and Au (17.67 µg/kg) were highest at Mogale City, Fleurhof, Krugersdorp, Shaft 17, and Davidsonville. These values reflected moderate to extreme contamination, supported by geoaccumulation index (Igeo), pollution load index (PLI), and contamination factor (Cfi) values. According to PCA, F1 was responsible for heavy metal generations from the local gold processing and waste dumping facilities. The F1 loading for Cd and Pb was 0.845 and 0.835, respectively, whereas F1 and F2 contribution of the variable % were greater than 0.70 for Ag, As, Au, Cd, Pb, Sn, Tl, and U, suggesting that they were generated from the waste dumps, transported by rain water and subsequently deposited in downstream soil. The heavy metal concentrations were traced upstream at the dumps where the highest averages were recorded, whereas the lowest values were measured from downstream samples. Thus, the gold mine tailing dumps are considered the primary sources of the high measured values of the heavy metals in the study sites. The ecological risk values were ranked in the order of As > Cd > Hg > Pb and exceeded the permissible health risk value suggested by the South African and global standards. Excessive Hg concentration with 160 ≤ Er i< 320 was recorded at Krugersdorp, whilst Pb with 320 ≤ Eri was recorded at Durban Deep. Thus, the estimated high Er i values insinuate higher ecological risk of heavy metals that can accumulate in the human body through absorption, inhalation and ingestion of dust, or ingestion of food grown from the contaminated soil.

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.

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)0.002
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.252
Teacher spread0.233 · 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