Quantitative Mineralogy and Geochemical Coherence Through Siroquant Validation: Implications For a Kaolinite-Gibbsite-Albite Occurrence in Heterogeneous Paleozoic Bedrock of the Iberian Massif (NW Spain)
Bibliographic record
Abstract
[EN] A multi-methodological approach that consists of the systematic integration of detailed mineralogical, micromorphological, and geochemical features has been used to characterize a number of heterogeneous siliceous Paleozoic materials including low- to very-low-grade metamorphic crystalline rocks and siliciclastic and other detrital materials Ordovician to Carboniferous in age. Included in the same sequence are black slates, quartzites, and shales with alternating beds of sandstone, mudstone, and, occasionally, intermediate coal beds. A set of complementary and sequential analyses was performed to confirm the primary mineral assemblages, particularly the presence of unusual secondary silicates in the clay fraction. The sequential mineralogical methods included microscopic petrographic analysis (MOP), scanning electron microscopy with energy dispersive X-ray spectrometry (SEM-EDS), and X-ray powder diffraction (XRPD). Major elements were analyzed by X-ray fluorescence spectrometry (XRF) and minor elements (in some cases) using inductively coupled plasma mass spectroscopy (ICP-MS). Mineral quantification was carried out using the Siroquant system which is based on the QXRPD Rietveld technique. The essential minerals are mainly represented by K-rich dioctahedral varieties of white mica (muscovite) or illite, Fe-rich chlorites (Mg-rich chamosites), plagioclases (albite), and quartz, occasionally with kaolinite or even gibbsite. Up to 12 trace minerals such as iron oxides and sulfides were identified in some assemblages. After performing a validation procedure, a high level of consistency was observed between the major element oxide percentages, inferred from the XRPD study, and the equivalent oxide proportions determined by direct chemical analysis. The strong linear correlation shows that the percentages of K2O, Na2O, and MgO are also consistent with the quantitative clay mineralogy. The abundance of albite and the presence of iron-rich chlorites, together with the identification of kaolinite and occasionally gibbsite, support the interpretation of these bedrock materials.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".