Decrypting the sulfur cycle in oceanic oxygen minimum zones
Bibliographic record
Abstract
Abstract Here we present ecophysiological studies of the anaerobic sulfide oxidizers considered critical to cryptic sulfur cycling in oceanic oxygen minimum zones (OMZs). We find that HS− oxidation rates by microorganisms in the Chilean OMZ offshore from Dichato are sufficiently rapid (18 nM h−1), even at HS− concentrations well below 100 nM, to oxidize all sulfide produced during sulfate reduction in OMZs. Even at 100 nM, HS− is well below published half-saturation concentrations and we conclude that the sulfide-oxidizing bacteria in OMZs (likely the SUP05/ARTIC96BD lineage of the gammaproteobacteria) have high-affinity (>105 g−1 wet cells h−1) sulfur uptake systems. These specific affinities for sulfide are higher than those recorded for any other organism on any other substrate. Such high affinities likely allow anaerobic sulfide oxidizers to maintain vanishingly low sulfide concentrations in OMZs driving marine cryptic sulfur cycling. If more broadly distributed, such high-affinity sulfur biochemistry could facilitate sulfide-based metabolisms and prominent S-cycles in many other ostensibly sulfide-free environments.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".