Petrogenesis and Metallotectonic Implications of the Middle–Late Jurassic Granitoids at the Chadi Cu Polymetallic Deposit, Southern Qin–Hang Belt (South China)
Bibliographic record
Abstract
Abstract Better understanding of shoshonitic rocks is vital to unravel the formation process and spatial distribution of their associated ore deposits. Here, we conducted analyses on the shoshonitic granodiorite and its mafic microgranular enclaves (MMEs) from the Chadi Cu‐Pb‐Zn polymetallic deposit (South China), with the aim to investigate their petrogenesis and tectonic setting. Zircon U‐Pb age of the MMEs (165.0 ± 1.2 Ma) is coeval with that of the host granodiorite (164.8 ± 0.63 Ma). The Chadi granitoids are enriched in large ion lithophile elements and light rare earth elements, but depleted in high‐field‐strength elements. The granodiorite displays low ( 87 Sr/ 86 Sr) i (0.7069–0.7072), and negative ε Nd ( t ) (–5.8 to –5.5) and zircon ε Hf ( t ) (–3.6 to –0.4) values. These isotopic characteristics of the granodiorite and MMEs indicate the mixing of a mafic magma (formed from the subduction‐related, metasomatically‐enriched lithospheric mantle) and a felsic magma (formed from the partial melting of crustal materials), which is closely related to the Paleo‐Pacific subduction. The Chadi granodioritic magma has likely low oxygen fugacity (<ΔFMQ + 1), low whole‐rock Sr/Y ratio (mostly < 30), and low S (0.04 ± 0.02 wt%) and Cl (0.23 ± 0.04 wt%) contents, suggesting that the potential of forming large‐scale Cu mineralization is low.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".