Textural and chemical zonation of pyrite at Pajingo: a potential vector to epithermal gold veins
Bibliographic record
Abstract
The Carboniferous Pajingo Epithermal System (PES) comprises several low sulphidation Au–Ag ore zones that have a total resource of c . 3 Moz (million ounces). The main Vera–Nancy vein is hosted by andesite that contains alteration which zones from inner silica–pyrite to argillic to distal propylitic alteration. Pyrite is ubiquitous in both alteration and vein. In the latter, pyrite is a minor component (<1%), but the dominant sulphide, and occurs as fine-grained (<50 μm) bands or disseminations. Coarse (up to 0.5 mm) euhedral pyrite is most abundant (up to 10%) in the silica–pyrite alteration whereas in argillic alteration pyrite (<50 to 250 μm) occurs as round to subhedral forms either as infill in narrow veinlets or as replacement. Fine-grained (<50 μm) pyrite occurs in propylitic alteration along rims of earlier mafic phenocrysts and has a low abundance (<1%). In-situ laser ablation inductively coupled plasma mass spectrometry was carried out on the pyrite in order to test the chemical variations between pyrite in different alteration zones. Results indicate that Mo and Ag concentrations vary over two orders of magnitude from the outer alteration zones (Mo c . 0.1 ppm; Ag c . 0.5 ppm) to the proximal vein alteration (Mo c . 30 ppm; Ag c . 20 ppm) whereas Pb displays an overall decrease from the hanging wall (a few hundred ppm) to the footwall (<100 ppm). Pyrite in the hanging- wall argillic alteration zone has Pb/Mo and Pb/Ag ratios of >100 whereas pyrite in silica–pyrite alteration zones has ratios of <100, and pyrite in silica–pyrite alteration zones immediately adjacent to the vein has Pb/Mo ratios of <30 and Pb/Ag ratios of <10. Thus, Pb/Mo and Pb/Ag ratios may provide a potentially powerful vector to epithermal gold veins in the PES and elsewhere.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".