Characterizing the structural diversity of a bacterial community associated with filter materials in recirculating aquaculture systems of <i>Scortum barcoo</i>
Bibliographic record
Abstract
The bacterial community structure associated with filter materials in the recirculating aquaculture system of Scortum barcoo was investigated using the 16S rRNA gene clone library method. Preliminary results showed that the clone library constructed from the initial operation condition was characterized by 31 taxa of bacteria belonging to eight phyla including Proteobacteria, Acidobacteria, Firmicutes, Fusobacteria, Sphingobacteria, Bacteroidetes, Verrucomicrobiae, and Actinobacteria. There were 14 taxa of bacteria belonging to four phyla including Proteobacteria, Acidobacteria, Planctomycetacia, and Nitrospirae from the stable operation condition where the water quality was well maintained. Nitrospirae was only found under the stable operation condition in this study. Our results further indicated that Nitrospira was dominated by members of the Nitrospira sp. lineages, with a minor fraction related to Nitrospira moscoviensis and an unknown Nitrospira cluster. These great differences of both diversity and composition between two operation conditions suggested that the composition of the microbial community varied with the degree of water quality in the recirculating aquaculture system of S. barcoo.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".