Application of Airborne, Laboratory, and Field Hyperspectral Methods to Mineral Exploration in the Canadian Arctic: Recognition and Characterization of Volcanogenic Massive Sulfide-Associated Hydrothermal Alteration in the Izok Lake Deposit Area, Nunavut, Canada
Bibliographic record
Abstract
We have investigated the application of ground, laboratory, and airborne optical remote sensing methods \nfor the detection of hydrothermal alteration zones associated with the Izok Lake volcanogenic massive sulfide \n(VMS) deposit in Nunavut, Canada. This bimodal-felsic Zn-Cu-Pb-Ag deposit is located above the tree line in \na subarctic environment where lichens are the dominant cryptogamic species coating the rocks. The immediate \nhost rhyolitic rocks have been hydrothermally altered and contain biotite, chlorite, and white micas as \ndominant alteration minerals. These minerals have spectral Al-OH and Fe-OH absorption features in the shortwave \ninfrared wavelength region that display wavelength shifts, which are documented to be due to chemical \ncompositional changes. Our ground spectrometer measurements indicate that there is a systematic trend in \nthe Fe-OH absorption feature wavelength position of biotite/chlorite with increasing distance from the VMS \ndeposit: the average Fe-OH absorption feature wavelength position of the proximal areas (398–3,146 m from \nmineralization) is observed at 2,254 nm, and that of the distal areas (5,782–6,812 m) at 2,251 nm. Moreover, \nthe proximal areas have an average Al-OH absorption feature wavelength position at 2,203 nm, in contrast with \nthe average wavelength position at 2,201 nm in the distal areas, implying a spectral shift of 2 nm. These findings \nindicate that hydrothermal alteration zones can be detected by hyperspectral remote sensing, despite the presence \nof abundant lichen cover. However, the airborne results discussed in this study required the screening out \nof more than 99% of the pixels in the area.
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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 | 0.001 | 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) | 0.001 | 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".