Pyrosequencing analysis of bacterial communities in Lake Bosten, a large brackish inland lake in the arid northwest of China
Bibliographic record
Abstract
The bacteria inhabiting brackish lake environments are poorly known, and there are few studies on the microbial diversity of these environments. Lake Bosten, a large brackish inland lake, is the largest lake in Xinjiang Province in northwestern China. Because sediments record past limnic changes, the analysis of sedimentary bacteria in Lake Bosten may help elucidate bacterial responses to environmental change. We employed 454 pyrosequencing to investigate the diversity and bacterial community composition in Lake Bosten. A total of 48 230 high-quality sequence reads with 16 314 operational taxonomic units were successfully obtained from the 4 selected samples, and they were numerically dominated by members of the Deltaproteobacteria (17.1%), Chloroflexi (16.1%), Betaproteobacteria (12.6%), Bacteroidetes (6.6%), and Firmicutes (5.7%) groups, accounting for more than 58.1% of the bacterial sequences. The sediment bacterial communities and diversity were consistently different along the 2 geographic environmental gradients: (i) freshwater-brackish water gradient and (ii) oligotrophic-mesotrophic habitat gradient. Deltaproteobacteria, Chloroflexi, and Betaproteobacteria were amplified throughout all of the sampling sites. More Bacteroidetes and Firmicutes were found near the Kaidu River estuary (site 14). Our investigation showed that Proteobacteria did not display any systematic change along the salinity gradient, and numerous 16S rRNA sequences could not be identified at the genus level. Our data will provide a better understanding of the diversity and distribution of bacteria in arid region brackish lakes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".