Laser ablation inductively coupled plasma mass spectrometry mapping of porphyry -related epidote from south-central British Columbia
Bibliographic record
Abstract
The microscopic composition of thirteen samples of epidote related to porphyry Cu mineralization was mapped using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) at the Geological Survey of Canada. The objective of this research is to improve the indicator mineral method of mineral exploration in glaciated terrains by utilizing the trace element composition of epidote. Six bedrock samples from porphyry Cu deposits of south-central British Columbia (Gibraltar, Mount Polley and Woodjam), three bedrock samples from the Nicola Group located close (<2 km) from the intrusions host of porphyry mineralization and afar (12 km), and four epidote grains from two till samples, one at Gibraltar and a second one at Mount Polley, were analyzed. Backscattered electron (BSE) images and the LA-ICP-MS maps show an heterogeneous distribution of Fe and Al in epidote following complex and mottled patterns and consistent zoning typically with high Fe and low Al concentrations in the core progressing to low Fe and high Al concentrations in the rim. Trace elements are heterogeneously distributed in epidote following the Fe/Al zoning in some samples. Evidence of late infiltration of trace elements (e.g. Cu, Zn, and REE) along fractures in epidote is observed in some samples. The variability in epidote composition is thought to be related to the changing conditions during its crystallization including oxidation state, pH, oxygen fugacity, fluid composition, temperature and pressure. Multiple LA-ICP-MS spot analyses need to be conducted on this mineral to fully evaluate its composition as an indicator mineral of porphyry Cu mineralization.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".