An exploratory study of “large‐ <i>n</i> ” detrital zircon geochronology of the Book Cliffs, <scp>UT</scp> via rapid (3 s/analysis) <scp>U–Pb</scp> dating
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Bibliographic record
Abstract
Abstract Detrital zircon (DZ) U–Pb geochronology has improved the way geologists approach questions of sediment provenance and stratigraphic age. However, there is debate about what constitutes an appropriate sample size (i.e., the number of dates in a DZ sample, n ), which depends on project objectives, sample complexity, and, critically, analytical budget. Additionally, there is ongoing concern about bias introduced by zircon grain size. We tested a recently developed rapid (3 s/analysis) data acquisition method by multicollector laser ablation‐inductively coupled plasma‐mass spectrometry (LA‐ICP‐MS) that incorporates an automated selection routine and calculates two‐dimensional grain geometry from polished sample surfaces. Eleven samples were analysed from below and above the Late Cretaceous (Campanian) basal Castlegate unconformity of the Book Cliffs, Utah, in a down‐depositional‐dip transect including Price, Horse, Tusher, and Thompson canyons. 12,448 new concordant dates were generated during two measurement sessions. Results are consistent with recent studies suggesting there is no major provenance change and little time (1–2 Myr) represented across the unconformity. Grain size and sample size both exert a strong control on sample dissimilarity. Age distributions constructed from subsamples of large grains are systematically less similar to whole samples; age distributions composed of small grains are overall more similar to whole samples. As such, North American sediment sources that produce large grains such as the Grenville and Yavapi‐Mazatzal belts can bias age distributions if only large grains are analysed. A sample size of n = 100 is inadequate for characterizing age distributions as complex as those of the Book Cliffs, whereas a sample size of n = 300 provides good characterization. Sample size of n ≈ 1000 or more is unnecessary unless project objectives include scanning for subordinate age groups, such as when identifying the youngest grains for calculating a maximum depositional age (MDA). Dates used in MDA calculations acquired with rapid acquisition are best re‐analysed with longer LA‐ICP‐MS acquisition methods or isotope dilution thermal ionization mass spectrometry for increased accuracy and precision. We include new MATLAB code and open‐source software programs, DZpick and DZmda , for automated spot picking and calculating MDAs.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it