Source‐To‐Sink Analysis in the Mesozoic SW Junggar Basin, Central Asia: Evidence From Detrital Garnet and Tourmaline Geochemistry
Bibliographic record
Abstract
Abstract Source‐to‐sink systems respond to and therefore potentially record topographic and tectonic changes. North of the Tian Shan Belt, the Sikeshu subbasin of the SW Junggar Basin transitioned from active extension in the Triassic to post‐extensional subsidence in the Jurassic‐Cretaceous. Sediment in the Sikeshu subbasin has been shown to be derived from the Tianshan. However, the details of the source‐to‐sink system remain unclear and discrepancies exist between proxy records. The heavy minerals in the Middle Triassic in the Sikeshu subbasin are dominated by garnets. To investigate the garnet sources and decipher the Mesozoic source‐to‐sink evolution, we conducted petrological and sedimentary analysis and detrital garnet and tourmaline geochemistry. We found that the geochemistry of garnets in the Middle Triassic sandstone is most consistent with that of the skarns in the Yili Block (YB) in Tianshan, while the geochemistry of 55%–84% of garnets in other Mesozoic sandstones is consistent with that of garnets in amphibolites in the YB. The geochemistry of the tourmalines since the Upper Triassic is consistent with that of the meta‐sedimentary rocks in the YB and Central Tianshan Block. The dominance of garnets sourced from skarns in the Middle Triassic probably indicates a near‐source point provenance and the broader range of garnet compositions from the Upper Triassic–Lower Cretaceous suggests multiple sources. We infer that the point source changed to multiple sources, which is consistent with the zircon spectra changing from unimodal to multimodal. This change reflects the expansion of the drainage that accompanies a change from active rifting to a post‐rift stage.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".