The<sup>40</sup>Ar‐<sup>39</sup>Ar laser analysis of K‐feldspar: Constraints on the uplift history of the Grenville Province in Ontario and New York
Bibliographic record
Abstract
A comprehensive geochronologic database describes a period of late extension across the Metasedimentary Belt (MB) of the Grenville Province in northeastern North America. Because extension continued through much of the young unroofing history of the region, these data do not bracket the timing of final extension across all shear zones and do not constrain the timing of final juxtaposition of terranes. Analysis of K‐feldspar in the MB by the40Ar‐39Ar method can give information on the very latest perturbations in the area since K‐feldspars have multiple, low closure temperatures, ranging from about 150° to 300°C. These multiple diffusion domains require temperature‐time modeling to fully interpret argon release spectra. This modeling requires precise knowledge of the temperature of degassing of each step, which usually requires the use of a resistance furnace for sample analysis. We establish a first‐order relationship between laser power and temperature, which can be used for multidiffusion domain modeling of K‐feldspars. Comparison of samples analyzed by both methods reveals virtually no difference between the systems, supporting the validity of K‐feldspar analyses by laser step heating. Our data suggest that using the laser for K‐feldspars can give results that are geologically reasonable, precise, and easier to collect. In this case, these data are then applied to the cooling history of the North American Grenville Province. Our K‐feldspar analyses show that the latest extensional motion along shear zones in the MB is after 900 Ma, and the region is uplifting as a uniform block by 780 Ma.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".