EPR Dating of Clay Minerals Formation Through Geological Times: Benchmarking From the Quaternary to the Neoproterozoic Era
Bibliographic record
Abstract
Revealing the environment and timing of clay formation in the geosphere is of major importance to understand and model the evolution of geological systems at the surface or near-surface of the continents, such as weathering covers, sedimentary basins or hydrothermal systems. Dating clay minerals by electron paramagnetic resonance spectroscopy (EPR) is a promising method that relies on the measurement of stable radiation-induced defects (RIDs) accumulating in their structure over time due to natural radioactivity. This approach has not yet been challenged by the inter-comparison with other geochronological methods, mostly because clay minerals accurately dated with methods independent from the EPR approach and also suitable for the EPR dating remain scarce in the geological record. Herein, an up-to-date protocol for the EPR dating and benchmarking are provided and developed by analyzing selected clay samples. The series includes a Mesoproterozoic illite (Thelon Basin, Canada), two paleosol kaolinites (Ukraine, Estonia) from at least late Ediacaran period, an Ypresian sedimentary kaolinite from the Aquitan Basin (France) and two Miocene and Pliocene kaolinites from lateritic duricrusts (Amazonia, Brazil). Despite some discussed uncertainties mainly related to the Th distribution in the samples, the time variation of dose rate and the thermal history of some clay samples, the EPR ages show a trend close to the 1/1 line with ages determined by other dating methods. These results bring promising support to the EPR dating methodology of clay minerals and extend its potential application field over a time-range spanning from Quaternary to Proterozoic.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".