Genetic diversity of<i>Sinorhizobium</i>populations recovered from different<i>Medicago</i>varieties cultivated in Tunisian soils
Bibliographic record
Abstract
A collection of 468 rhizobial isolates was obtained from different ecological areas of Tunisia by trapping them on Medicago sativa cv. Gabes, Medicago scutelleta cv. Kelson, Medicago truncatula, and Medicago ciliaris. A subsample of 134 rhizobia was chosen to determine their plasmid profile, and 89 isolates were subjected to multilocus enzyme electrophoresis (MLEE) and PCR/RFLP analysis using 16S, IGS (inter genic spacer), and nifKD probes. Twenty-five representatives from these isolates were evaluated for their nodulation and nitrogen fixation capacities. MLEE studies revealed two groups with highly heterogeneous host specificity and geographical origin. The discriminatory power was found to be slightly better with the amplified ribosomal intergenic region, than the nifKD genes. Divisions detected by nifKD amplified DNA analysis matched those established by ribosomal PCR- RFLPs. The comparison between different analyses revealed that MLEE illustrated better phenotypic properties of isolates than PCR-RFLP or plasmid content analysis. Clear distinction between Sinorhizobium meliloti and Sinorhizobium medicae were observed by analysis of the IGS symbiotic regions between nifD and nifK genes. Were able to distinguish three inoculation groups; isolates trapped from M. sativa cv. Gabes and M. scutelleta cv. Kelson formed one inoculation group which was more closely related to isolates trapped from M. truncatula than those trapped from M. ciliaris.
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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".