Mycorrhizal-Bacterial Amelioration of Plant Abiotic and Biotic Stress
Bibliographic record
Abstract
Soil microbiota plays an important role in the sustainable production of the different types of agrosystems. Among the members of the plant microbiota, mycorrhizal fungi (MF) and plant growth-promoting bacteria (PGPB) interact in rhizospheric environments leading to additive and/or synergistic effects on plant growth and heath. In this manuscript, the main mechanisms used by MF and PGPB to facilitate plant growth are reviewed, including the improvement of nutrient uptake, and the reduction of ethylene levels or biocontrol of potential pathogens, under both normal and stressful conditions due to abiotic or biotic factors. Finally, it is necessary to expand both research and field use of bioinoculants based on these components and take advantage of their beneficial interactions with plants to alleviate plant stress and improve plant growth and production to satisfy the demand for food for an ever-increasing human population.
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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 | 0.000 | 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 | 0.000 |
| 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".