Large non-mass-dependent iron isotope fractionation in an oxic-anoxic transition zone of lake sediments
Bibliographic record
Abstract
Laboratory studies detected non-mass-dependent Fe-isotope fractionation during magnetotactic-bacteria-controlled iron (III) reduction, suggesting its potential as a biomineralization proxy. In nature, the preservation of the non-mass-dependent Fe-isotope signature may be difficult due to the abundance of other Fe-rich materials. Here we report a set of distinctly large non-mass-dependent Fe-isotope composition in the top 6.5 cm of the oxic-anoxic transition zone from a sediment core of Lake Aha, southwestern China. Negative ∆'57Fed-δ'56Fed and positive ∆'57Fed-[Mn] correlations support that an abundance of manganese (IV) and ongoing sulfate reduction created a zone of Fe-limited porewaters in the top 6.5 cm of the sediment where magnetotactic bacteria thrived. Non-mass-dependent Fe-isotope signatures were not detected in a sediment core taken at a nearby site in the same lake where in the oxic-anoxic transition zone porewater Fe concentrations were orders-of-magnitude higher. The discovery of non-mass-dependent Fe-isotope signatures in natural sediment offers clues to detecting similar biosignatures. Natural occurrence of large non-mass-dependent iron isotope fractionation was discovered in sediments of Lake Aha, southwestern China, where the magnetotactic bacteria thrived top centimeters are iron concentration limited in pore water due to abundant manganese (IV) and ongoing sulphate reduction.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".