Phylogenetic and physiological diversity of dissimilatory ferric iron reducers in sediments of the polluted Scheldt estuary, Northwest Europe
Bibliographic record
Abstract
The potential for dissimilatory ferric iron [Fe(III)] reduction in intertidal sediments of the polluted Scheldt estuary, Northwest Europe, was assessed by combining field-based geochemical measurements with laboratory experiments on the associated microbiology. Microbial communities at a freshwater and brackish location were characterized by culture-independent 16S rRNA gene analysis, as well as enrichments, strain isolation and physiological screening. Dilution-to-extinction batch enrichments using a variety of Fe(III) sources were performed. The dilution factor of the inoculum in the enrichments had a more determining effect on the Fe(III)-reducing microbial community structure than the Fe(III) source. Well-known Fe(III) reducers, including members of the family Geobacteraceae and the genus Shewanella, constituted only a small fraction (< or = 1%) of the in situ microbial community. Instead, facultative anaerobic Ralstonia and strictly anaerobic, spore-forming Clostridium species dominated Fe(III) reduction. These species were able to utilize a variety of electron acceptors. This flexibility may help the organisms to survive in the dynamic estuarine environment. The high diversity and abundance of culturable Fe(III) reducers (4.6 x 10(5) and 2.4 x 10(4) cells g(-1) sediment at the freshwater and brackish site respectively), plus the high concentrations of chemically reducible solid-phase Fe(III) at the sites, implied a high potential for dissimilatory Fe(III) reduction in the estuarine sediments. Pore water chemical data further supported in situ dissimilatory Fe(III) reduction.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".