Extending the Grazing Season with Mixtures of Spring-Planted Spring and Winter Cereals
Bibliographic record
Abstract
The objective of the study was to extend the grazing season into the fall using crop-combinations of spring-planted spring and winter cereals. Treatments established at Lacombe, Alberta, Canada were spring oat (Avena sativa L.) and barley (Hordeum vulgare L.) monocrops (SMC), spring-planted winter wheat (Tritcum aestivum L.) and winter triticale (X Triticosecale Wittmack) monocrops (WMC), spring and winter cereal binary mixtures seeded together in the spring (MX) and the winter cereal seeded after the first clipping of the spring cereal (double crop-DC). Clippings were carried out at 4 to 6 wk intervals after the initial cut (Boot and Late Milk Stage). MX produced more total yield than other systems when cut initially at the Late Milk stage ( 92% of SMC at initial cut and 65% of WMC for regrowth). MX was superior to DC and SMC for regrowth yield, but not WMC. Treatments containing winter triticale were superior to those containing winter wheat for fall regrowth. Cropping systems like MX have the potential to economically extend the grazing season in the parkland of the Canadian prairies.
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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".