Contribution of <i>Medicago sativa</i> to the productivity and nutritive value of forage in semi‐arid grassland pastures
Bibliographic record
Abstract
Abstract The inclusion of legumes in semi‐arid native grasslands may promote the productivity and nutritive value of forage. This study was designed to assess the effect of legumes (the introduced legume Medicago sativa or the native legume Dalea purpurea) and soil P fertility (addition of 0, 50, or 200 P2O5 kg/ha at seeding) on the dry matter and nutrient content of native grasses mixtures, compared with the commonly used introduced forage grass Bromus biebersteinii grown with M. sativa. Plant harvests were performed in September 2008, July 2009 and September 2009. Plants nutrient content, δ15N value and dry matter were analysed. Results show that the M. sativa enhanced the N and P concentrations of native grass mixtures early in the summer, as well as the N concentration in Bouteloua gracilis in late summer of the driest year, 2009. The higher AM fungal diversity promoted by M. sativa was positively correlated with the dry matter and nitrogen uptake of M. sativa and with the P concentration of native grasses, in early summer. Overall, this study shows that M. sativa promoted beneficial AM fungal taxa and improved forage production in the semi‐arid prairies.
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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".