Combining Nd isotopes in monazite and Hf isotopes in zircon to understand complex open-system processes in granitic magmas
Bibliographic record
Abstract
Abstract Mapping the age and trace element and Sm-Nd isotope compositions of monazite grains from a peraluminous Cretaceous granite using laser ablation–split stream analysis reveals a wide range in Nd isotope and rare earth element (REE) compositions within and between single grains. These data corroborate isotopic variability indicated by Hf isotope analysis of zircon in the same granite sample. The REE variations indicate that monazite grew during fractional crystallization. Hf and Nd isotopes indicate that the granitic magma was generated from at least two distinct Proterozoic sources of approximately the same age: one component that had highly radiogenic initial 176Hf/177Hf and 143Nd/144Nd and a second component that was notably less radiogenic. This study highlights the utility of in situ REE and Sm-Nd isotope data in monazite in magmatic systems. Further, it refines the zircon-based constraints on magmatic processes because of sensitivity of light REEs to fractional crystallization, lower probability of complications owing to inheritance, and smaller analytical volumes required.
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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 | 0.000 | 0.000 |
| 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".