Atypical Diagenesis and Geochemistry of Redox-Sensitive Elements in Hydrothermal Sediments of the Southern Okinawa Trough
Bibliographic record
Abstract
Early diagenesis processes and the geochemistry of redox-sensitive elements (RSEs) in four sediment cores in an active hydrothermal field in the southern Okinawa Trough (OT) was investigated. Dissolved Fe, Mn, ΣHS–, and several other RSEs (Mo, U, and V) in pore water were measured. We also studied metal distribution in sediments using sequential extraction methods. Very high dissolved Fe concentrations (∼140 μmol L–1) but insignificant dissolved Mn were observed in surficial pore waters in the station adjacent to the hydrothermal vent, where highly reactive Fe, Mo, U in the sediments were also measured. Such an atypical diagenetic sequence found in those cores could be driven by the overwhelmingly high reactive Fe fraction (mostly Fe oxides) delivered from the vents. Consequently, significant upward benthic fluxes of Fe and Mo were estimated for the studied stations. In addition, we performed a principal component analysis (PCA), together with relative ratios of carbonate-related elements (Sr, Ca, Mg), to identify particles’ origins in the hydrothermal field; two endmembers being the hydrothermal source and hydrogenous processes. This comprehensive study on a unique set of samples collected by advanced technology provided valuable data to demonstrate distinctive geochemical features that occur in hydrothermal sediments.
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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 | 0.001 | 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 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".