Vertical and horizontal distribution of sediment nitrite-dependent methane-oxidizing organisms in a mesotrophic freshwater reservoir
Bibliographic record
Abstract
In the present study, we investigated the spatial change of sediment nitrite-dependent anaerobic methane-oxidizing (n-damo) organisms in the mesotrophic freshwater Gaozhou Reservoir (6 different sampling locations and 2 sediment depths (0–5 cm, 5–10 cm)), one of the largest drinking water reservoirs in China. The abundance of sediment n-damo bacteria was quantified using quantitative polymerase chain reaction assay, while the richness, diversity, and composition of n-damo pmoA gene sequences were characterized using clone library analysis. Vertical and horizontal changes in sediment n-damo bacterial abundance occurred in Gaozhou Reservoir, with 1.37 × 105 to 8.24 × 105 n-damo 16S rRNA gene copies per gram of dry sediment. Considerable horizontal and vertical variations of n-damo pmoA gene diversity (Shannon index = 0.32–2.50) and composition also occurred in this reservoir. Various types of sediment n-damo pmoA genes existed in Gaozhou Reservoir. A small proportion of n-damo pmoA gene sequences (19.1%) were related to those recovered from “Candidatus Methylomirabilis oxyfera”. Our results suggested that sediment n-damo pmoA gene diversity might be regulated by nitrite, while n-damo pmoA gene richness might be governed by multiple environmental factors, including total organic carbon, total phosphorus, nitrite, and total nitrogen.
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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 | 0.000 | 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".