Petrogenesis of Ore-Hosting Diorite in the Zaorendao Gold Deposit at the Tongren-Xiahe-Hezuo Polymetallic District, West Qinling, China
Bibliographic record
Abstract
The newly discovered Zaorendao gold deposit is in the Tongren-Xiahe-Hezuo polymetallic district in the westernmost West Qinling orogenic belt. The estimated pre-mining resource is approximately 13.6 t of Au at an average grade of 3.02 g/t. Mineralization is predominantly controlled by NW-trending and EW-trending faults within diorite intrusions and surrounding sedimentary rocks. In the present study, in situ zircon U–Pb geochronology and Lu–Hf isotopic analyses of the ore-hosting diorite at Zaorendao were measured using LA-ICP-MS. The data suggest that the diorite was emplaced at ca. 246.5 ± 1.9 Ma. The large variation of zircon Hf isotopic composition (ɛHf(t) values ranging from −12.0 to −1.8) indicates a two-stage model age (TDM2) that ranges from 1.4 Ga to 2.0 Ga. Such Lu–Hf isotopic compositions indicate that the diorite was dominantly derived from a Paleo- to Meso-Proterozoic continental crust. The wide range of εHf(t) and the presence of inherited zircon can be interpreted to suggest the mixing of Paleo- to Meso-Proterozoic continental crust with a mantle component. Combining such characteristics with the geochemistry of coeval rocks that are associated with the diorite, we therefore proposed that the gold-hosting Triassic diorite in the Zaorendao gold deposit formed in an active continental margin that was associated with the northward subduction of the paleo-Tethyan ocean.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".