Phenanthrene-degrading <i>Sphingobium xenophagum</i> are widely distributed in the western Pacific Ocean
Bibliographic record
Abstract
Six phenanthrene-degrading bacteria were isolated from surface seawater sampled from the western Pacific Ocean. They were identified as Sphingobium xenophagum (formerly Sphingomonas xenophaga) based on morphological, biochemical, and chemical characteristics, and 16S rRNA sequences. The salinity ranges for the growth of these isolates were broader than those of the seven reported Sphingomonas strains isolated from soil, and the optimum NaCl concentration in the growth medium was higher than that for soil sphingomonads. These isolates also exhibited higher phenanthrene-degrading activity under briny conditions than that of a phenanthrene-degrading Sphingomonas strain isolated from soil. A DNA fragment carrying nah genes, which are encoded on the naphthalene-catabolic plasmid NAH of Pseudomonas putida PpG7, hybridised less strongly with the total DNA of all isolates. Certain genes involved in phenanthrene degradation were also preliminarily characterised in all isolates. This is the first demonstration that S. xenophagum strains, which are able to degrade phenanthrene, are widely distributed in marine environments, and that the growth and phenanthrene-degrading activity of these strains are adapted to briny conditions. The results also suggest that genes for phenanthrene degradation, which are dissimilar to nah genes, were also ubiquitously distributed in marine strains.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".