Red clover varieties show nitrogen fixing advantage during the early stages of seedling development
Bibliographic record
Abstract
Plant and environmental factors affect root nitrogen (N) exudation dynamics in legumes. To better understand the genotypic variability and plant factors affecting root N release nodulation, plant growth, tissue N content, and root N exudation, six (three diploid and three tetraploid) red clover (Trifolium pratense L.) varieties were evaluated under controlled environmental conditions during the first 8 wk of plant growth after rhizobia inoculation. Genotypic differences were found for nodulation, plant dry weight (DW), leaf area, root attributes (root length, surface area, volume, and diameter), shoot and root N concentration, and N content. Genotypic differences were also found for root exudate N content in terms of NO3−-N, NH4+-N, and dissolved organic N (DON). In general, root exudate inorganic N content was greater in tetraploid varieties than in the diploids throughout the growth period. Root exudate DON content was greater than the inorganic N content. The NO3−-N content in root exudate was positively correlated with root growth attributes and root N concentration, whereas NH4+-N content was positively correlated with nodule number. Root exudate DON was positively correlated with shoot N concentration and average nodule DW. These results highlight the existence of genotypic differences among red clover varieties for plant morphological factors affecting root N release during the early stages of plant development.
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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".