Nitrogen to Sulfur Ratio in Tifton 85 Bermudagrass in Five Cuttings in 2004
Bibliographic record
Abstract
Background.The response of Tifton 85 bermudagrass to sulfur (S) was evaluated in a potassium rate and source at two N-rates study that was adequately fertilized with 180 Ib P Z 0 5 /ac disked into the Darco soil at initiation of the study in 2001.In 2002, 2003, and 2004, an additional 120 Ib of P 2 0 5 /ac/yr as triple superphosphate (0-46-0) was surface-applied at growth initiation of the Tifton 85 bermudagrass each spring.Potassium sources were potassium chloride (KCI, 0-0-62-47% Cl), potassium sulfate (K 2 S0 4 , 0-0-50-17.6%S), and KCl plus elemental S.Potassium rates from all sources were 0, 134, 268, and 402 Ib/ac as K 2 0 split-applied one-third at growth initiation and one-third each following two in-season harvests to lOx 18-ft plots that received 80 or 160 Ib of N/ac for each bermudagrass regrowth during the 2004 growing season.Sulfur as K 2 S0 4 was applied at rates of 47, 94, and 142 Ib/ac.Equal S rates were applied as granular elemental S (Dispersal, 90% S) in the KCl + S treatments.Yield data and samples of Tifton 85 plant material were collected from each plot at each harvest for dry matter/chemical analysis using a Swift Machine forage plot harvester (Swift Current, Saskatchewan Canada.)Plant samples were dried at 60°C, ground in a Wiley mill to < 20-mesh, and analyzed for S in a VarioMax CNS analyzer, (Elementar Americas Inc, NJ).
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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 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".