Detecting Buried Porphyry Cu Mineralization in a Glaciated Landscape: A Case Study from the Gibraltar Cu-Mo Deposit, British Columbia, Canada
Bibliographic record
Abstract
Abstract At the Gibraltar porphyry Cu-Mo deposit in south-central British Columbia, Canada, geochemical and mineralogical anomalies in till around a cluster of mineral occurrences form amoeboid-shaped dispersal patterns controlled by three phases of ice movement. The glacial dispersal patterns defined by elevated concentrations of ore (Cu, Mo) and pathfinder (Ag, Zn) elements and alteration oxides (Al2O3, K2O) in the till matrix (clay and silt plus clay fractions) extend over areas of 6–36 km2 and are centered on the main economic mineralization. Mineralogical dispersal trains were identified by the high abundances of chalcopyrite, pyrite, jarosite, titanite, and epidote, which were derived from the mineralization and its associated oxidation and alteration zones. These mineralogical anomalies in till extend approximately 30 km2 for chalcopyrite, 62 km2 for jarosite, and up to 136 km2 for epidote. Epidote grains in till with a trace element composition of >10 ppm As, >4 ppm Sb, <200 ppm total rare earth elements (ΣREEs), <45 ppm Y, <100 ppm Sc + Cr + Y, and/or <2 ppm Th + Hf are interpreted as being either principally derived from the intrusive rocks or from hydrothermal alteration of the porphyry mineralization. Rare epidote grains with >30 ppm Cu, interpreted to be related to the porphyry Cu mineralization, were detected in till up to 7 km down-ice from the economic mineralization. This study demonstrates that till geochemistry and mineralogy, combined with geochemical analyses of specific minerals such as epidote, are efficient methods for identifying porphyry Cu mineralization in terrains covered by glacial sediments.
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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) | 0.020 | 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".