Performance of Timothy‐based Grass/Legume Mixtures in Cold Winter Region
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This study sought to identify grass/legume mixtures that increase the yield and persistence of forage stands with improved nutritive quality in cold‐winter regions, compared with the standard mixture of timothy ( Phleum pratense L.)/red clover ( Trifolium pratense L.)/alsike clover ( Trifolium hybridum L.). Timothy was mixed with either perennial ryegrass ( Lolium perenne L.), meadow fescue ( Festuca pratensis L.) or Kentucky bluegrass ( Poa pratensis L.). The legumes in mixtures were red clover, alfalfa ( Medicago sativa L.) or white clover ( Trifolium repens L.). Averaged over three production years, the majority of mixtures had greater dry matter (DM) yields than the standard (8.35 t ha −1 ). Timothy, grown alone and in three mixtures, outyielded the standard by 19–30 %. Yield reductions in mixtures over the 3‐year period were greatest with red clover, and least with bluegrass. Mixtures with alfalfa were highest in nitrogen (28.4 g kg −1 ), while grasses grown alone (24.6 g kg −1 ) and the standard mixture (25.1 g kg −1 ) were the lowest in N. Mixtures with red clover or alfalfa had the least neutral detergent fibre (NDF), averaging 418 and 429 g kg −1 respectively. Mixtures including white clover were initially low in NDF at 347 g kg −1 in year 1 but increased to 550 g kg −1 in year 3 as white clover composition declined in the sward.
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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 it