A comparative study assessing variety and management effects on C4 perennial grasses in a northern climate
Bibliographic record
Abstract
In the province of Ontario, Canada, markets are emerging for biomass for a range of end-uses including combustion, gasification and bio-products. Given concerns over the technical feasibility and sustainability of crop residue removal, dedicated C4 perennial grasses were identified as potential candidates to meet this emerging demand. In 2008, a multi-site trial was initiated across the province to comparatively evaluate C4 perennial grasses, including miscanthus (Miscanthus spp.), switchgrass (Panicum virgatum) and big bluestem (Andropogon gerardii). Four varieties of miscanthus (M. sinensis × M. sacchariflorus - Nagara, Amuri, M1 Select and Polish) were compared to two upland varieties of switchgrass (Cave-in-Rock and Shelter), two varieties of big bluestem (Prairieview and Southlow), and one variety of prairie cordgrass (Red River). Treatments were set up in a factorial experiment with four nitrogen rates (0, 40, 80, 160 kg N ha-1) and two harvest dates (late fall and early spring). A treatment representing the prominent land use pattern in the region was also included to assess land use change effects and relative biomass yield. Data is given for measurements taken to assess treatment effects on establishment success, winter survival, yield and moisture content. Variation in winter tolerance was observed, but it can be concluded that varieties for each of the evaluated species exist that are adapted and suitable to be grown under Ontario conditions. For many of the measured parameters, including yield, significant interactions between year, location, species, variety, and agronomic management were observed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".