Indicator-mineral content of bedrock and till at the Gibraltar porphyry Cu-Mo deposit and the Woodjam porphyry Cu-Au-Mo prospect, south-central British Columbia
Bibliographic record
Abstract
The next generation of porphyry Cu deposits to be discovered in the Canadian Cordillera are likely to be found underlying glacial sediments. The recovery of minerals diagnostic of porphyry Cu mineralization, termed porphyry Cu indicator minerals (PCIM), in till and stream sediments will contribute to the discovery of buried mineralization. To identify minerals that have the potential to be used as PCIM, thirteen bedrock samples from the Gibraltar porphyry Cu-Mo deposit and ten from the Woodjam porphyry Cu-Au-Mo prospect were examined after producing mid-density (2.8-3.2 SG) and heavy (>3.2 SG) mineral concentrates. Chalcopyrite, a common Cu ore mineral, is abundant in bedrock and till in the Gibraltar and Woodjam areas making it a key PCIM. Jarosite, common in leached cap and supergene zones of porphyry Cu deposits, is generally more abundant in till near the known mineralized zones compared to surrounding regions and therefore, should be considered a PCIM diagnostic of the oxidized portion of porphyry mineralization. Other Cu (azurite, malachite, covellite, chalcocite) and Mo (molybdenite) minerals are present in mineralized bedrock but are rare or absent in till, limiting their utility as PCIM at these two study sites, but they could be important PCIM if found in detrital sediments at other sites. Other minerals (e.g. tourmaline, apatite and rutile) present in till and bedrock need to be characterized geochemically in order to be classified and used as PCIM.
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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) | 0.002 | 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".