Tracing Metal Sources of Geogas with Lead Isotopes: A Case Study on the Bairendaba Silver‐polymetallic Deposit, Inner Mongolia
Bibliographic record
Abstract
Abstract Geogas survey is an unconventional geochemical prospecting method that has proven particularly effective in exploring concealed ore deposits. However, its application in covered areas has been questioned due to the lack of a confirmed geogas formation mechanism. Investigating the sources of geogas anomalies can help clarify this mechanism. This study focuses on the Bairendaba silver‐polymetallic deposit, located in a grassland‐covered area. Tracer research was conducted on lead isotope compositions in the mining area by analyzing various solid media (soil, rocks, ores) and geogas samples. The results revealed considerable differences in lead isotope compositions between background geogas samples and solid media. Furthermore, the lead isotope compositions of anomalous geogas samples differed markedly from those of background samples. These anomalous samples are located closer to the ore body, suggesting that ore‐derived lead is incorporated into the geogas. The anomalous lead in geogas is inferred to originate from deep, concealed ore bodies. This study provides a theoretical basis for applying geogas surveys in mineral exploration within covered terrains.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".