Hyperspectral reflectance spectrometry in the exploration for VMS deposits using the Izok Lake Zn-Cu-Pb-Ag deposit, Nunavut as a test site
Bibliographic record
Abstract
We have investigated the application of ground, laboratory and airborne optical remote sensing methods to the detection of hydrothermal alteration zones associated with volcanogenic massive sulphide (VMS) deposits using the Izok Lake Zn-Cu-Pb-Ag deposit, Nunavut as a test site. The deposit is located in a subarctic environment where lichens are abundant on the rock outcrops. The rhyolitic host rocks to the deposit have been hydrothermally altered and contain white mica and chlorite group minerals. These alteration minerals have Al-OH and Fe-OH absorption features in the short-wave infrared (SWIR) wavelength region. The absorption feature wavelength positions can shift as a function of chemical compositional changes within minerals. In and around the Izok Lake deposit there are systematic trends in the Al-OH and Fe-OH absorption feature wavelength positions with distance from the massive sulphide lenses. Furthermore, these trends can be detected in bulk rock lithogeochemical data. Our results demonstrate the feasibility of using hyperspectral remotely sensed data to delineate hydrothermal alteration zones and determine alteration intensity in high-latitude regions.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".