Scheelite bearing veins with enrichment of light rare earth elements (Lree's) from Hutti Gold Mines, Eastern Dharwar Craton, India
Bibliographic record
Abstract
India has a >200 years long history of gold mining and the giant Kolar Gold Fields in the Eastern Dharwar Craton (EDC) which had previously produced >1000t of Au from gold ore zones, strongly indicate that the geology is eminently favourable for hosting large amounts of native gold along with multi-minerals (Silver, Tungsten and Cobalt) and Light Rare Earth Elements (LREE) as well as invisible gold in pyrites. We have used an in-situ technique, Laser Ablation-Inductively Coupled Plasma Mass Spectrometry (LA-ICPMS) to analyse the Scheelite occurring within quartz veins within the alteration zones of the world class Hutti Gold Mine of M/s. Hutti Gold Mines Co Ltd (HGML) in the EDC. The scheelite samples from Hutti are enriched in light rare earth elements up to 10.93 ppm and depleted in heavy rare earth elements up to 6.13 ppm, coupled with positive to negative Europium anomalies. The total REE (“ REE +Y) in the scheelite samples is 35.34 ppm and the ratio of LREE/HREE is 1.72. Scheelite REE binary pattern shows a positive correlation between MREE and HREE suggesting a strong influence of granitic fluids and data suggest that the Hutti deposit corroborates petrogenetically well with the Archean gold deposits occurring in Canada, Australia and China.
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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 | 0.000 | 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".