A Preliminary Evaluation of Lablab Biomass Productivity in Virginia
Bibliographic record
Abstract
A field study was conducted for two years with seventeen lablab [Lablab purpureus (L.) Sweet] lines to characterize its productivity under Virginia’s agro-climatic conditions and to determine lablab’s potential as a forage crop. One sample per replication (0.3 m row length) was harvested approximately 90 days after planting to record fresh weight. These samples were dried to a constant weight to record dry weights. Dry and fresh yields were not affected by lines and year of production. Overall means of fresh and dry yields varied from 47 to 91 with a mean of 62, and 9 to 15 with a mean of 13 Mg/ha, respectively. Year of production had significant effects on concentrations of P, K, S, Mg, Mn, Cu, and Zn. Concentrations of protein, P, K, Ca, Mg, S, Al, B, Cu, Fe, Mn, Na, and Zn in lablab produced in Virginia were 15, 0.28, 2.30, 1.32, 0.27, 0.22, 224, 20, 18, 343, 79, 0.03, and 40, respectively. Quality of lablab forage compared well with literature values of other forage legumes especially alfalfa. Lablab biomass in this study contained 60, 45, and 15 percent ADF, NDF, and lignin, respectively indicating that it may also be a potential feedstock for bio-ethanol manufacture.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".