Occurrence of Sesquioxide in a Mid-Low Grade Collophane-Sedimentary Apatite Ore from Guizhou, China
Bibliographic record
Abstract
Checking the presence of sesquioxide (Fe2O3, Al2O3) is helpful for its removal in advance. Therefore, the occurrence of sesquioxide in a mid-low grade calcareous-siliceous collophane ore (massive carbonate-apatite, also known as francolite) from Guizhou, China was determined by X-ray fluorescence spectroscopy (XRF), X-ray diffraction (XRD), field emission scanning electron microscope-energy dispersive X-ray spectrometry (FESEM-EDX) and Mineral Liberation Analyzer (MLA). The results show that iron mainly occurs as pyrite FeS2, goethite FeO(OH) and as substitution within dolomite Ca(Mg,Fe)(CO3)2, while aluminum is enriched in muscovite KAl2(AlSi3O10)(OH)2 and also found in apatite (F,CO3)CaPO4 and calcite CaCO3 due to isomorphism or adsorption. All these minerals are fine-grained, among which pyrite and goethite tend to be enriched in larger particles. Intergrowth is predominant in the six minerals’ locking. Pyrite is mainly intergrown with calcite, biotite and also included in apatite and muscovite, while the monomer pyrite appears as semi-automorphic fine grain with the liberation of 56.1%. Apatite particles are mainly intergrown with quartz and calcite. Most of goethite, dolomite, muscovite and calcite form intergrowth with apatite, with contents of 21.7%, 11.1%, 19.5% and 41%, respectively. The removal of pyrite, goethite, dolomite, muscovite and calcite in the ore is the key to reduce the contents of Fe2O3 and Al2O3. In the subsequent beneficiation, the ore must be fully ground. In addition to flotation, magnetic separation can also be considered to remove part of iron in ore. For the removal of aluminum from apatite, leaching method can be considered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".