A Growing Degree Day Model to Schedule Trinexapac‐ethyl Applications on <i>Agrostis stolonifera</i> Golf Putting Greens
Why this work is in the frame
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Bibliographic record
Abstract
Trinexapac‐ethyl (TE) is a widely used growth regulator in the turfgrass industry. Poor summer efficacy has been related to more rapid metabolism in the plant. The purpose of this study was to determine if a growing degree day (GDD) model could be used to identify the optimum TE reapplication interval for putting greens. This objective was accomplished through model development and validation. Model development was conducted on a creeping bentgrass ( Agrostis stolonifera L.) golf putting green in Madison, WI, during 2008. The treatments consisted of five TE reapplication intervals (100, 200, 400, 800 GDD, and 4 wk) and a control. Growing degree days were calculated in degrees C with a base temperature of 0°C. Trinexapac‐ethyl was applied at the rate of 0.05 kg a.i. ha −1 . Clippings were collected daily. The 100‐ and 200‐GDD reapplication intervals provided consistent 20 and 12% yield suppression, respectively. Other reapplication intervals had alternating periods of yield reduction followed by yield enhancement. Model validation occurred on a different creeping bentgrass green in 2009 and 2010. The experiment was a 3 × 2 factorial CRD with three TE rates (0.00, 0.05, and 0.10 kg a.i. ha −1 ) and two reapplication frequencies (200 GDD and 4 wk). The 200‐GDD interval consistently suppressed clipping yield. Application rate had no effect on the duration of suppression. Reapplying TE every 200 GDD provides more consistent growth regulation than a calendar‐based application schedule.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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