Focus on the Role of the Abiotic Environment on Interactions Between Plants and Microbes
Bibliographic record
Abstract
Interactions between plants and microbes are shaped by the physical world that surrounds them. In nature, the abiotic environment is complex, and factors such as nutrient and water availability, humidity, wind, carbon dioxide levels, salt, pollutants, and temperature all affect the growth and physiology of plants and microbes as well as their interactions. Much of our mechanistic understanding of plant-microbe interactions comes from experiments done in carefully controlled conditions. This Focus Issue looks at how aspects of the abiotic environment affect these plant-microbe interactions, and, conversely, how plant-microbe interactions affect host response to abiotic stress. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2022. Additional content is available on the Focus on the Role of the Abiotic Environment on Interactions Between Plants and Microbes. Complete Genome Sequence of Curtobacterium sp. C1, a Beneficial Endophyte with the Potential for In-Plant Salinity Stress Alleviation Proteasomal Degradation of JAZ9 by Salt- and Drought-Induced Ring Finger 1 During Pathogen Infection
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".