Current and residual effects of nitrogen fertilizer applied to grass pasture on production of beef cattle in central Saskatchewan
Bibliographic record
Abstract
Four rates of nitrogen fertilizer (0, 50, 100 and 200 kg N ha-1) were applied for 4 yr to two replications of a 32-yr-old crested wheatgrass (Agropyron cristatum) pasture at Lanigan, Saskatchewan, after which no fertilizer was applied for a further 4 yr. The pastures were grazed by pregnant yearling Hereford heifers using a “put-and-take” stocking system. Soil cores (0–60 cm) were taken to monitor soil NO3-N concentrations either in early spring, before grass growth commenced, or in late fall, after grass growth had ceased. Pasture measurements included available forage at the start of the grazing season, total forage production and the concentrations of crude protein, acid detergent fiber (ADF), ash, Ca, P, Mg, K, Cu, Zn, Fe and Mn. Heifers, fistulated at the esophagus, were used in 1984 and 1985 to obtain samples of the grazed herbage, which were analyzed for organic matter digestibility (OMD), protein and minerals, except P and K. Heifer intakes of digestible organic matter (DOMI), protein and minerals, except P and K, were estimated from their concentrations in fistula extrusa and estimates of intake obtained from extrusa digestibility and fecal output using Cr2O3 as a fecal marker. Phosphorus intake was estimated from fecal P concentration. Plasma samples were also collected and analyzed for concentrations of minerals.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".