Customized Spectral Libraries for Effective Mineral Exploration: Mining National Mineral Collections
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Infrared (Visible-Near Infrared-Shortwave Infrared (VNIR-SWIR)) spectroscopy is a cost-effective technique for mineral identification in the field. Modern hand-held spectrometers are equipped with on-board spectral libraries that enable rapid, qualitative analysis of most minerals and facilitate recognition of key alteration minerals for exploration. Spectral libraries can be general or customized for specific mineral deposit environments. To this end, careful collection of spectra in a controlled environment on pure specimens of key minerals was completed using the National Mineral Reference Collection (NMC) of the Geological Survey of Canada. The spectra collected from specimens in the ‘Kodama Clay Collection’ were processed using spectral plotting software and each new example was validated before being added to a group of spectra considered for incorporation into the on-board library of the handheld ASD-TerraSpec Halo near-infrared (NIR) mineral identification instrument. Spectra from an additional suite of mineral samples of the NMC containing REE , U, Th, and/or Nb are being prepared for a new, publicly available spectral library. These minerals commonly occur in carbonatite or alkali intrusive deposits, and as such will assist in the exploration for critical metals.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it