Redistribution of heat‐producing elements during melting of Archean crust
Bibliographic record
Abstract
Abstract Heat generated from the decay of K, Th, and U plays a fundamental role in the differentiation and stabilization of Earth's continental crust. This is particularly important in the construction of Archean cratons that form the nuclei of Earth's continents. The Kapuskasing uplift is a rare exposure of an Archean‐age crustal cross‐section that provides a snapshot of crustal melting, differentiation, and compositional stratification. We integrate field observations, whole‐rock compositions, thermodynamic equilibrium and accessory mineral modelling with heat production and latency time modelling to provide insights into the partitioning of heat‐producing elements between residue and melt during anatexis of metabasites as well as the resulting effects on metamorphic timescales and the production of tonalite–trondhjemite–granodiorite (TTG) suites. We model six metabasite compositions ranging from relatively fertile greenschist facies metabasites to melt‐depleted residual mafic (upper‐)amphibolites to granulites. Heat‐producing elements are modelled to be partitioned between melt and residue; the dominant minerals in the residue that host these elements are apatite, hornblende, K‐feldspar, and epidote. At 800–850°C epidote is no longer stable, and the melt fraction is predicted to contain roughly half of the heat production capacity for the system. Apatite and melt are expected to be the dominant repositories for Th and U during anatexis; zircon is predicted to be completely consumed by 850°C, whereas apatite persists to higher temperatures and allanite is expected only in minor modal abundances at high‐P, low‐T conditions. The partitioning of heat‐producing elements into relatively low‐density melt decreases the heat production of the residual system during anatexis. Due to their high density and affinity for U and Th, epidote and apatite retain heat production capacity in the residue during metabasite melting. Thermal latency modelling of metamorphism suggests that enriched metabasite compositions require 38–46 My to increase the temperature from ~650 to 850°C (solidus temperature to peak metamorphic temperature of the Kapuskasing uplift), whereas estimates are considerably shorter for depleted compositions (7–25 My). Four of the six samples modelled require 60–70 My to reach 1000°C from the solidus. Our modelling of heat‐producing element partitioning and predicted proportions of melt suggest that enriched basaltic compositions are the most reasonable source of TTG magmas and our heating time modelling indicates the mantle as an equal to dominant source of heat for metabasite anatexis compared with radiogenic heat production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".