The Application of Near-Infrared Spectral Analysis in Exploration of Gold Mine in Bilihe
Bibliographic record
Abstract
Near-Infrared Spectral Mineral Analysis technology has already become one of the most important methods in the mineral exploration in the developed countries,such as Australia,Canada and US.This technology can rapidly identify alteration minerals and their combinations,and such can reveal significant information about mineralization.A BJKF-1 type Near-Infrared Spectral Mineral Analyzer,made by Nanjing Institute of Geology Mineral Resources,was used to investigate alteration minerals collected from Bilihe gold mine in Inner-Mongolia.The results indicated that this analyzer can efficiently recognize 5 types of alteration mineral,montmorillonite,illite,quartz,sericite,kaolinite,and the distribution characteristics of the alteration minerals can be estimated by the location of absorptive peaks and the intensity of peak values.According to the distribution characteristics of the 5 kinds of alteration mineral,we predicted that the Southwestern,the Northwestern of Bilihe gold mine and the NW-SE extension area of the 26th lode are the areas of stronger alteration and of being apt to mineralize.
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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 | 0.000 | 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".