Geochemical Classification and Determination of Maturity Source Weathering in Beach Sands of Eastern San’ in Coast, Tango Peninsula, and Wakasa Bay, Japan
Why this work is in the frame
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Bibliographic record
Abstract
<span style="font-size: 10.5pt; font-family: 'Times New Roman','serif'; mso-bidi-font-size: 10.0pt; mso-fareast-font-family: 宋体; mso-font-kerning: 1.0pt; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">Geochemistry of beach sand sediments collected from the Eastern San’in coast (n=17), Tango Peninsula (n=14) and Wakasa Bay (n=7) shorelines were investigated using XRF analyses for major and trace elements to characterize their composition, classification, maturity, provenance, tectonic setting and degree of weathering in source areas. Investigated sands from all sites were very similar showing depletion in all elements except SiO<sub>2</sub>, K<sub>2</sub>O and As relative to the UCCN and JUCN, suggesting a moderate geochemical maturation. Beach sand sediments from these locations can be classified as arkose, subarkose and litharenite that are chemically immature and formed under arid/semi-arid conditions with a tendency towards increasing chemical maturity suggesting that they are from multiple sources. The relatively low to moderate values of weathering indices of Chemical Index of Alteration (CIA), Plagioclase Index of Alteration (PIA) and Chemical Index of Weathering (CIW), the beach sands from all sites in the source area have undergone low to moderate degree of chemical weathering. A-CN-K and A-CNK-FM plots, which suggest a granitic source composition, also confirm that the sand samples from these sites have undergone low to moderate degree of chemical weathering in consistent with CIA, PIA and CIW values. A plot of the analyzed beach sands data on the provenance discriminating function F1/F2 showed that most of the investigated beach sand sediments in all locations fall within mafic to intermediate ocean island arc source; similar to the tectonic setting discrimination diagrams based on major elements suggesting a passive margin.</span>
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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