Overseeding and Trinexapac-ethyl Effects on Tolerance to Simulated Traffic of Four Bermudagrass Cultivars Grown as a Sand-based Athletic Field
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Bibliographic record
Abstract
Common bermudagrass ( Cynodon dactylon ) and hybrid bermudagrass ( Cynodon dactylon var. dactylon × C. transvaalensis ) often are used for athletic fields as a result of their wear tolerance and recuperative ability. A wear tolerance study was conducted May 2007 through Nov. 2008 in Lexington, KY. Plots were managed as athletic turf and simulated traffic was applied during the Kentucky high school football seasons. The cultivars Quickstand, Tifway 419, Riviera, and Yukon grown in a sand-based medium were evaluated. Trinexapac-ethyl (TE) was applied at label rates and frequencies or left untreated. Overseeding treatments were perennial ryegrass ( Lolium perenne ) at 0, 546, and 1093 lb/acre pure live seed. Traffic treatments were applied with a Brinkman traffic simulator three times per week, once each Monday, Wednesday, and Friday, without regard to soil moisture status or weather for the periods 10 Sept. to 2 Nov. 2007 and 12 Sept. to 14 Nov. 2008. In both years of the study, the main effect of cultivar was significant ( P < 0.05) in traffic tolerance (‘Tifway 419’ = ‘Riviera’ > ‘Quickstand’ = ‘Yukon’). Overseeding at the medium and high rates also provided significantly greater turf cover for the coarse-textured, more open cultivars (Quickstand and Yukon) over the fine-textured, more dense cultivars (Riviera and Tifway 419). Applications of TE did not significantly improve tolerance to simulated athletic traffic in either year of the study regardless of cultivar or overseeding treatment. Within the parameters of this study, data indicate that only cultivar has significant effects on tolerance to simulated traffic on a sand-based field. Overseeding treatments for the fine-textured, more dense cultivars and TE applications on sand-based field systems had no positive significant effects on tolerance to simulated traffic.
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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 it