How Can Technical Aspects Help Improving K-Ar Isotopic Data of Illite-Rich Clay Materials into Meaningful Ages? The Case of the Dominique Peter Uranium Deposit (Saskatchewan, Canada)
Bibliographic record
Abstract
Previously published K-Ar dating results of <2 μm illite separates from uranium-hosting and associated barren rocks from Dominique Peter district of the Carswell circular structure in the Athabasca Basin (Canada) were considered to trace four distinct tectonic-thermal events at 1447 ± 45, 1282 ± 40 and 1184 ± 15 (all errors at ± 2 Ma, with a younger, less constrained episode at ~900 Ma. Recent analyses of K-Ar ages of additional <0.2 μm illite fractions from a few initial samples demonstrate that the intermediate ages at ~1280 and ~1185 Ma result, in fact, from mixing of two generations of illite that precipitated at ~1450 and ~900 Ma. They have, therefore, no stratigraphic value, while the two tectonic-thermal episodes at 1448 ± 48 and 937 ± 39 Ma appear to be historically sound. In fact, the analytical procedure of isotopic dating clay materials is of more importance than is often stated. For instance, a safe way to evaluate and constrain best numerical isotopic data of clay separates into ages is combining data of two size splits from several samples. If such age data, especially from size fractions of indurated host rocks, are scattered and point towards the higher data of the coarser fractions, they are potentially enriched in earlier crystallized K-rich components, and should consequently be discarded. The occurrence of detrital or early-crystallized components in clay-rich separates becomes a serious concern when comparing ages generated by various isotopic methods on mineral separates of various whole rocks. It is especially verified in very old, metal-rich deposits such as the uranium-rich deposits of the Saskatchewan Basin. These deposits and their host rocks were studied extensively by a large spectrum of isotopic methods on many types of rocks in a widely dispersed area, and for which the numerical statistics became, sometimes, more central in the interpretation than the specificity of the successive events in the host rocks.
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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 | 0.025 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".