Geochemical and Volcanological Criteria in Assessing the Links between Volcanism and VMS Deposits: A Case on the Iberian Pyrite Belt, Spain
Bibliographic record
Abstract
VMS deposits in the Iberian Pyrite Belt (IPB), Spain and Portugal, constitute the largest accumulation of these deposits on Earth. Although several factors account for their genetic interpretation, a link between volcanism and mineralization is generally accepted. In many VMS districts, research is focused on the geochemical discrimination between barren and fertile volcanic rocks, these latter being a proxy of VMS mineralization. Additionally, the volcanological study of igneous successions sheds light on the environment at which volcanic rocks were emplaced, showing an emplacement depth consistent with that required for VMS formation. We describe a case on the El Almendro–Villanueva de los Castillejos (EAVC) succession, Spanish IPB, where abundant felsic volcanic rocks occur. According to the available evidence, their geochemical features, εNd signature and U–Pb dates suggest a possible link to VMS deposits. However, (paleo)volcanological evidence here indicates pyroclastic emplacement in a shallow water environment. We infer that such a shallow environment precluded VMS generation, a conclusion that is consistent with the absence of massive deposits all along this area. We also show that this interpretation lends additional support to previous models of the whole IPB, suggesting that compartmentalization of the belt had a major role in determining the sites of VMS deposition.
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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 | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".