Molecular and physiological comparison of<i>Azospirillum</i>spp. isolated from<i>Rhizoctonia solani</i>mycelia, wheat rhizosphere, and human skin wounds
Bibliographic record
Abstract
Four phenotypically similar bacterial strains isolated from fungal, plant, and human sources were identified as Azospirillum species. Strains RC1 and LOD4 were isolated from the mycelium of the apple root pathogen Rhizoctonia solani AG 5 and from the rhizosphere of wheat grown in apple orchard soil, respectively. Strains C610 and F4626 isolated from human wounds were previously misclassified as Roseomonas genomospecies 3 and 6. All four strains demonstrated close similarities in 16S rRNA gene sequences, having > or =97% identity to Azospirillum brasilense type strain ATCC 29145 and <90% identity to Roseomonas gilardii, the Roseomonas type strain. Extensive phenotypic similarities among the four strains included the ability of free-living cells to fix N2. Cells of strains RC1, LOD4, and C610 but not of strain F4626 could be induced to flocculate by incubation with 10 mmol.L-1 glycerol or fructose in medium containing 0.5 mmol.L-1 NO3-. Our results indicate a wide range of potential sources for Azospirillum spp. with the isolation of Azospirillum spp. from human wounds warranting further investigation.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".