Multivariate statistical analysis of lodgepole pine outer bark samples for metallic mineral exploration within the southern Nechako Plateau, British Columbia, Canada
Bibliographic record
Abstract
Mining and exploration is an important economic sector within British Columbia and Canada. Biogeochemical mineral exploration is one method that assists in the discovery of economic mineral deposits. The interpretation of biogeochemical data, however, is more complex than conventional exploration samples as it depends on a plant’s interaction with its environment. To reveal patterns related to molybdenum and gold mineralization, multivariate statistical analysis was applied to two suites of biogeochemical samples collected from lodgepole pine outer bark in the southern Nechako Plateau of British Columbia. These samples were collected as part of the Geological Survey of Canada’s Nechako National Mapping Project (from 1996-1998) and a British Columbia Geological Survey’s Interior Plateau Geoscience Project in 1994. One suite of samples contained anomalous molybdenum concentrations and is located proximal to the Endako molybdenum mine. The second suite is anomalous for gold and is within the vicinity of the Blackwater-Davidson gold project. The samples were analysed by instrumental neutron activation analysis for 28 elements, treated as compositions using the log-ratio approach and investigated for their element associations using RQ-mode principal component analysis. Twenty-four elements were chosen in the molybdenum dataset, based on Exploratory Data Analysis, for further statistical procedures. Twenty-five elements were chosen in the gold dataset. Principal Component Analysis identified a number of distinct element associations. The first principal component, from both datasets, shows a complex relationship between plant element uptake and soil composition. Principal component 2 (molybdenum dataset) revealed that molybdenum-cobalt associations in lodgepole pine outer bark may be an indicator of molybdenum mineralization for the southern Nechako Plateau, whereas principal component 2 (gold dataset) revealed the association between gold and arsenic as an indicator of gold mineralization. Further studies are suggested with respect to the nature of molybdenum-cobalt, gold-arsenic, zinc, arsenic-antimony and caesium enrichment within the study area and using principal component analysis on high dimensional, low sample size data.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".