The Role of Recycled Oceanic Crust in the Generation of Alkaline A‐Type Granites
Bibliographic record
Abstract
Abstract Melting and dehydration of subducted oceanic slabs dominate element recycling within the subduction factory, but the role of recycled oceanic crust in the source of intraplate magmas is poorly understood. In situ zircon O‐Hf isotope data from two Early Cretaceous alkaline A‐type granites that are genetically related to large‐scale extension of eastern China in the Late Mesozoic (circa 125 Ma) yield low δ18O (1.8 ± 0.3‰ to 5.1 ± 0.3‰, 2σ) and positive εHf(t) (1.5 ± 1.2 to 17 ± 1.2, 2σ). This suggests the contribution of altered oceanic crust and an enriched mantle component in the source region. Elevated initial 87Sr/86Sr and 206Pb/204Pb ratios, and εHf(t) whole rock values with relatively constant εNd(t) values beyond the normal mantle array, require a component that underwent seawater interaction in the source of protolith. The geochemical data require a complex source region for the alkaline A‐type granites in NE China involving more than 40% recycled oceanic crust. This altered oceanic crust beneath the Late Mesozoic lithospheric mantle likely represents remnants of multiple subduction and collision events between microblocks from the Late Paleozoic to Early Mesozoic in northeastern China. Recycling of subducted oceanic crust represents a novel exotic source for the origin of alkaline A‐type granites in intraplate extensional settings.
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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 | 0.000 |
| 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".