Production of Phaseolus vulgaris L. Genotypes with Tithonia diversifolia (Hemsl.) Gray and Cajanus cajan (L.) Millsp.
Bibliographic record
Abstract
Adding mulch biomass prior to crop seeding may improve production of tropical soil. We evaluated the response of four bean (Phaseolus vulgaris L.) genotypes to the addition of mulch biomass from Tithonia diversifolia (Hemsl.) Gray and Cajanus cajan L. Millsp. The addition of mulch did not result in significant differences (p < 0.05) in soil characteristics when compared to a control (no mulch addition) except for soil potassium (K), which was significantly greater (p < 0.05) in the T. diversifolia mulch biomass treatment. Bean yield and shoot biomass were significantly greater (p < 0.05) in the mulch biomass treatments compared to the control (no biomass added). In these treatments, Phosphorus (P)-efficient bean genotypes had a significantly greater (p < 0.05) yield and shoot biomass. Bean shoot nutrient concentrations were significantly different (p < 0.05) between mulch biomass treatments and between bean genotypes (P, K and magnesium (Mg) only). Phosphorus utilization and uptake efficiencies were significantly different (p < 0.05) between mulch biomass treatments and between bean genotypes. Bean root biomass was not significantly different (p < 0.05) between mulch biomass treatments, but was significantly different (p < 0.05) between bean genotypes. The number of root nodules was significantly greater (p < 0.05) in the T. diversifolia mulch biomass treatment and was significantly different between bean genotypes.
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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 | 0.000 | 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 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".