MétaCan
Menu
Back to cohort
Record W3114602890 · doi:10.22067/econg.v12i2.77113

Trace elements geochemistry of galena in fluorite deposits from central Alborz, Mazandaran Province

2020· article· en· W3114602890 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeochemistry and Elemental Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGalenaFluoriteGeochemistryGeologyTRACE (psycholinguistics)MineralogyChemistryRadiochemistryMetallurgySphaleritePyriteMaterials science

Abstract

fetched live from OpenAlex

Introduction Trace elements including As, Sb, Bi, Ga, Ge, In, Hg, Cd, Tl, Se and REEs have special applications in various industries due to their physical and chemical properties. Ore deposits of these metals have not occurred in the Earth's crust, and these elements are mainly hosted in sulfide minerals of Cu, Pb and Zn (Hall and Heyl, 1968; Song and Tan, 1996; Ye et al., 2011; George et al., 2015). Elika Formation (middle Triassic) in central Alborz is host of several carbonate rock-hosted fluorite deposits such as Kamarposht, Pachi-Miana, Shashroodbar and Era (Alirezaee, 1989; Rastad and Shariatmadar, 2001; Rajabi et al., 2013; Vahabzadeh et al., 2014; Zabihitabar and Shafiei, 2014; Mehraban et al. 2016; Nabiloo et al. 2017). Despite previous valuable studies in these deposits, the value of the presence of trace elements in the galena of these deposits has not yet been documented. Materials and methods For the current research study, sampling from 3 flourite mines including Kamarposht, Pachi-Miana and Era was carried out to collect 26 pure galena grains separated from various fluorite ore-types. The samples were analyzed for trace elements at the ICP-MS at Act Labs Ltd., Canada. Results The highest concentrations of trace elements in galena samples were obtained for Sb (with mean 692 ppm and maximum concentration of 2531 ppm) and Ag (with a mean of 24.28 ppm and a maximum concentration of 2531 ppm). The lowest values were obtained for Bi (mean 0.04 ppm), Se (average 1.89 ppm) and Ga (mean 0.9 ppm) and Tl (mean 0.3 ppm). Hg (0.06 – 10 ppm), Cd (1.14 – 23 ppm) and As (0.1 – 36 ppm) exhibited a wide range of concentrations. The comparison of the trace elements concentration in the studied galena samples with those of the MVT, SEDEX, Irish-type deposits shows that the concentrations of Sb, Tl, Hg, Se and Cu in the studied galena are close to the values for MVT deposits, whereas the studied galena samples are much poorer in Ag, Bi, Cd and As than those of the MVT deposits. There is meaningful relationship between concentrations of some trace elements such as Tl– Ag (r=0.82), Tl– Cu (r=0.71), Ag–Sb (r=0.66), Cu– Ag, Ag – As, Cu– As, Sb– Cu, Hg – Zn, As – Sb, Hg – Cd, Zn – Cu (0.3 < r < 0.6). Discussion Our data revealed that galena samples are relatively rich in Sb (up to 2581 ppm with an average ~ 620 ppm) and Ag (up to 70 ppm with an average ~ 30 ppm), whereas they are poor in other trace elements. Inter-element relationships in galena show strong correlation between Sb – Ag (r≥0.65) and moderate correlation between Ag – As, Ag –Cu as well as Hg –Zn (0.4<r<0.6). Based on our data, high concentration of Sb and Ag in galena could be related to the presence of special minerals (e.g., tetrahedrite, stephanite, diaphorite, twinnite) as inclusion in the host galena, whereas the occurrence of not very high concentrations of Cd and Hg and meaningful relationship with Zn concentrations in galena could be due to the presence of inclusions of sphalerite (ZnS) and polhemusite (ZnHgS) in the galena. Due to the large presence of galena (several tens of thousands) in the studied fluorite mines, and the relatively high concentration of Sb and Ag in the galena samples of these deposits, an assessment of the economic recovery on a laboratory scale of these elements is suggested.

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)0.000
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 score0.156
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0390.000

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 head0.102
GPT teacher head0.424
Teacher spread0.323 · 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.

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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicGeochemistry and Elemental AnalysisFrench-language works237,207