Minimal gene set from <i>Sinorhizobium</i> ( <i>Ensifer</i> ) <i>meliloti</i> pSymA required for efficient symbiosis with <i>Medicago</i>
Bibliographic record
Abstract
Significance Modern agriculture is dependent on the yearly application of large quantities of nitrogen fertilizer acquired via the chemical fixation of N 2 in the Haber–Bosch process. More sustainable agricultural systems take advantage of biological nitrogen fixation, particularly the symbiosis between nitrogen-fixing bacteria called rhizobia and leguminous plants. A long-term goal of symbiotic nitrogen-fixation (SNF) research is to optimize its use in agriculture by improving rhizobia or by engineering symbiotic relationships into nonlegumes. Using the model rhizobium Sinorhizobium ( Ensifer ) meliloti , we establish that only 58 genes from the 1.35-Mb pSymA megaplasmid are required for effective SNF. This minimal SNF gene set, and genetic platform, have important implications for engineering approaches to optimize rhizobia inoculants and transfer symbiotic abilities to novel backgrounds.
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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 | 0.000 | 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 | 0.001 |
| 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".