New observations by X-ray fluorescencemicroscopy provide insights for the origin ofAguablanca sulfide-matrix breccias in SW Spain
Bibliographic record
Abstract
Sulfide-matrix breccia ores are common features of deposits hosted within mafic conduit-style intrusions. They account for a large proportion of Ni-Cu sulfiderich ores in a number of deposits including the sub-layer and offset dyke deposits at Sudbury (Lightfoot, 2016), deep portions of the feeder dyke system and margins of the Ovoid and Eastern Deeps orebodies at Voisey’s Bay, (Barnes et al., 2017), Nebo-Babel (Seat et al., 2007) and particularly in the subject of this contribution, the Aguablanca deposit in SW Spain (Pina, 2019). Genetic interpretations of sulfide matrix breccias have fallen into four main categories (Barnes et al. 2019): tectonic “durchbewegung” origins, upward emplacement of sulfide-rich slurries due to late stage compression in intrusive complexes, downward emplacement as sulfiderich gravity flows during backflow in sill-dyke complexes or into footwall offset dykes, and gravity-driven downward percolation of sulfide liquid through the matrix of original silicate-matrix intrusion breccias. This study presents microbeam XRF mapping to reveal petrographic features, textures and chemical zoning patterns in Aguablanca sulfide-matrix breccia ores at a scale of mm-cm.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".