Th/U ratios in metamorphic zircon
Bibliographic record
Abstract
Abstract The Th/U ratios of zircon crystals are routinely used to help understand their growth mechanism. Despite the wide application of Th/U ratios in understanding the geological significance of zircon U–Pb ages, the main controls on the Th/U ratio in metamorphic zircon are poorly understood. Here, phase equilibria modelling coupled with solubility expressions for accessory minerals are used to investigate the controls on the Th/U ratios of suprasolidus metamorphic zircon in an average amphibolite facies metapelite composition. We also present a new database of metamorphic Th/U ratios in zircon from Western Australia. Several factors affecting the Th/U ratio are investigated, including the bulk rock concentrations of Th and U, the amount of monazite in the system, and open v. closed system behaviour. Our modelling predicts that the main controls on the Th/U ratio of suprasolidus metamorphic zircon are the concentrations of Th and U in the system, and the breakdown and growth of monazite in equilibrium with zircon. Furthermore, the relative timing of zircon and monazite growth during cooling and melt crystallization has an important role in the Th/U ratio of zircon. Early grown zircon near the peak of metamorphism is expected to have elevated Th/U ratios whereas zircon that grew near the solidus is predicted to have relatively low Th/U ratios, which reflects the coeval growth of monazite during cooling and melt crystallization. Our modelling approach aims to provide an improved understanding of the main controls of Th/U in metamorphic zircon in migmatites and hence better apply this geochemical ratio as a tool to assist in interpretation of the genesis of metamorphic zircon.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".