Microbial Engineering of Floc Fe and Trace Element Geochemistry in a Circumneutral, Remote Lake
Bibliographic record
Abstract
Evaluation of lacustrine floc Fe, Pb, and Cd biogeochemistry over seasonal (summer, winter) and water column depth (metalimnetic, hypolimnetic) scales reveals depth-independent seasonally significant differences in floc Fe biominerals and trace element (TE: Pb, Cd) sequestration, driven by floc microbial community shifts. Winter floc [TE] were significantly lower than summer [TE], driven by declining abundance and reactivity of floc amorphous Fe((III))-(oxy)hydroxide (FeOOH) phases under ice ([FeOOH](summer) = 37-77 mgg(-1) vs [FeOOH](winter) = 0.3-7 mgg(-1)). Further, while high summer floc [FeOOH] was observed at both water column depths, winter floc was dominated by Fe((II)) phases. However, the observed seasonal change in the nature and concentrations of floc Fe-phases was independent of water column [Fe], O2, and pH and, instead, significantly correlated to floc bacterial community membership. Bioinformatic modeling (Unifrac, PCA analyses) of in situ and experimental microcosm results identified a temperature-driven seasonal turnover of floc microbial communities, shifting from dominantly putative Fe metabolisms within summer floc to wintertime ancillary Fe reducing and S metabolizing bacteria. This seasonal shift of floc microbial community functioning, significantly the wintertime loss of microbial Fe((II))-oxidizing capability and concomitant increases of sulfur-reducing bacteria, alters dominant floc Fe minerals from Fe((III)) to Fe((II)) phases. This resulted in decreased winter floc [TE], not predicted by water column geochemistry.
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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 | 0.000 | 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 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".