Mineral markers of porphyry copper mineralization: progress report on the evaluation of tourmaline as an indicator mineral
Bibliographic record
Abstract
Tourmaline is considered a potential indicator of porphyry-style mineralization as it is a relatively common accessory mineral and has a broad range of compositions. The aim of this study is to test discrimination criteria for tourmaline in relation to porphyry copper mineralization. Work to date has focussed on the collection of tourmaline in bedrock samples from a broad range of known porphyry deposits, the detailed examination of tourmaline in archived till samples from the vicinity of the Woodjam deposit, and the collection of new bedrock and stream sediment samples in the area of the Casino deposit. Three different types of tourmaline were identified in bedrock from Casino: i) breccia-style; ii) vein-style; and iii) disseminated. A paragenetic analysis based on associated minerals and tourmaline textures indicates that tourmaline is one of the first hydrothermal minerals to form in the mineralized porphyry system. Diffusion-like textures found in some tourmaline grains from bedrock samples from other deposits is significant because chemical diffusion in tourmaline is considered to be virtually non-existent. Future work includes the completion of trace element analysis of tourmaline, comparison of tourmaline chemical signatures in bedrock to those recovered in till or stream sediments at the two test sites, and investigation of Fe2+/Fe3+ using Raman spectroscopy.
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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 | 0.000 |
| 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".