Potassium isotope composition in global loess: Origins and implications
Bibliographic record
Abstract
Potassium (K) isotope compositions (δ 41 K) in global loess deposits can provide valuable insights into the average upper continental crust (UCC). However, current knowledge of δ 41 K in the UCC is limited due to the lithological complexity of the continental crust , which results in highly variable K isotope compositions. Accurately estimating the K isotope composition of the UCC remains a challenge. Here, we investigated the concentration, phase, and isotopic composition of K in loess samples from Asia , Europe, Oceania , North America, and South America to identify the dominant controls on loess δ 41 K and better constrain the average composition of the UCC. Our results show that the δ 41 K value in globally compiled loess ranges from −0.60 ± 0.08 ‰ to −0.33 ± 0.04 ‰, with an average of −0.46 ± 0.12 ‰ (2 S.D.). This loess-based δ 41 K value of the average UCC is comparable to the average δ 41 K value established from various crustal materials by Huang et al. (2020). Nonetheless, our new range is slightly narrower compared with the previous estimation. We infer the measured K isotope variation in loess reflects a result of eolian sorting rather than chemical weathering. The abundance of 39 K-rich illite is the primary driver of the δ 41 K variability in these loess samples. We suggest that the K isotope composition in bulk loess record provide more reliable information of the grain size sorting effect and thus inferring regional wind patterns (e.g., past monsoon variation).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".