Seasonal changes in bacterial communities associated with healthy and diseased <i>Porites</i> coral in southern Taiwan
Bibliographic record
Abstract
We compared the bacterial communities associated with healthy scleractinian coral Porites sp. with those associated with coral infected with pink spot syndrome harvested during summer and winter from waters off the coast of southern Taiwan. Members of the bacterial community associated with the coral were characterized by means of denaturing gradient gel electrophoresis (DGGE) of a short region of the 16S rRNA gene and clone library analysis. Of 5 different areas of the 16S rRNA gene, we demonstrated that the V3 hypervariable region is most suited to represent the coral-associated bacterial community. The DNA sequences of 26 distinct bands extracted from DGGE gels and 269 sequences of the 16S rRNA gene from clone libraries were determined. We found that the communities present in diseased coral were more heterogeneous than the bacterial communities of uninfected coral. In addition, bacterial communities associated with coral harvested in the summer were more diverse than those associated with coral collected in winter, regardless of the health status of the coral. Our study suggested that the compositions of coral-associated bacteria communities are complex, and the population of bacteria varies greatly between seasons and in coral of differing health status.
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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".