Iron Loss During Continental Weathering in the Early Carboniferous Period Recorded by Karst Bauxites
Bibliographic record
Abstract
Abstract Significant iron (Fe) loss can occur during continental weathering and efflux to the ocean via runoff, historically affecting global Fe cycling and marine ecosystems. Here, we report extremely low Fe content in early Carboniferous (ca. 340 Ma) bauxites in southwestern China. These bauxites were formed by redeposition of terrestrial soils along the paleo‐continental margin of the western South China Plate in warm climates. The bauxites contain high δ56Fe (−0.17‰ to +1.15‰) values with a negative correlation between Fe2O3 and δ56Fe, indicating that a substantial amount of Fe(III) was reduced to isotopically light dissolved Fe(II) and effuxed to the ocean via reductive dissolution under anoxic conditions. The low Corg content and low FeHR/FeT, Mo/Al, U/Al, and V/Al ratios of bauxite suggest that this reduction process occurred during the pedogenic (continental weathering) rather than the depositional/diagenetic stage of karst bauxite formation. Most of the dissolved Fe(II) were rapidly re‐oxidized to Fe(III) and transported toward the paleo‐continental margin forming iron ores with δ56Fe values around zero (−0.13‰ to +0.16‰). The negative correlation between Al2O3 and Fe2O3 contents in global karst bauxites suggests common Fe loss processes during continental weathering in geological periods favoring karst bauxite formation, such as during the Carboniferous, Permian, and Cretaceous periods and the Cenozoic era. Karst bauxite may thus provide a record of Fe loss during continental weathering and act as an indicator of enhanced Fe flux to oceans.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".