Above-ground net primary production of plains rough fescue [Festuca hallii (Vasey) Piper] after a single defoliation on five landform elements
Bibliographic record
Abstract
Pantel, A., Romo, J. T. and Bai, Y. 2011. Above-ground net primary production of plains rough fescue [ Festuca hallii (Vasey) Piper] after a single defoliation on five landform elements. Can. J. Plant Sci. 91: 689–696. Above-ground net primary production (ANPP) was determined for plains rough fescue [Festuca hallii (Vasey) Piper] following a single defoliation to 7.5 cm stubble height on five landform elements in the Northern Mixed Prairie. The landform elements included north aspect-concave slopes, north aspect-convex slopes, south aspect-concave slopes, south aspect-convex slopes, and level uplands. Above-ground net primary production was determined for 2 yr after defoliating plants in May through November. Above-ground net primary production after defoliation was not dependent on landform elements in the first (P=0.23) and second years (P=0.22) after defoliation. In the first year after June through September defoliation, ANPP was reduced 29 to 41% (P <0.01), whereas May, October, or November defoliation had no significant effect on ANPP. Above-ground net primary production did not vary significantly (P=0.61) among months of defoliation in the second year after defoliation. Less ANPP in the first year after June through September defoliation indicates the need for ≥1 yr of deferred use to allow plants to regain their production potential. Unaffected ANPP after May, October, or November defoliation suggests plains rough fescue can be grazed annually. Recuperation of ANPP after defoliation depends on the month of the year in which plains rough fescue is defoliated, but not on landform elements in the Northern Mixed Prairie.
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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".