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Record W3099238546 · doi:10.5539/ijc.v13n1p1

Optimization of Nitric Acid Leaching of Rare Earth Elements From Moroccan Natural Phosphate

2020· article· en· W3099238546 on OpenAlex
Marouane Amine, Fatima Asafar, L. Bilali, M. Nadifiyine

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.

venuePublished in a venue whose home country is Canada.
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

VenueInternational Journal of Chemistry · 2020
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryLeaching (pedology)Nitric acidRare earthPhosphateRare-earth elementInorganic chemistryNuclear chemistryMineralogyOrganic chemistrySoil scienceGeology

Abstract

fetched live from OpenAlex

Phosphate is a very important natural resource in Morocco and one of the secondary resources of rare earth elements. Our study is particularly interested in Youssoufia phosphate, which contains 228.77 ppm of rare earth elements (ΣREEs). The purpose of our work is to study the influence of different parameters (acid concentration, solid/liquid ratio and temperature) in order to determine the optimal conditions for the leaching of rare earths. An experimental design (Doehlert matrix) has been drawn up to optimize the experimental conditions of the leaching. All tests were made with nitric acid at different concentrations varying between 1.5M and 4.5M with a solid/liquid ratio of 1/12 to 1/6; reaction temperature and duration are respectively 20°C to 80 °C and 60 min. The optimal conditions are obtained when using 69 °C as temperature, 4.1 M as acid concentration and 1/9 as solid/liquid ratio.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.239
Teacher spread0.230 · 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