Effects of Ice Cover on Annual Bluegrass and Creeping Bentgrass Putting Greens
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Damage as a result of ice cover on putting greens affects golf courses in cold climates. The objectives of this study were to assess cold‐hardiness levels and injury of annual bluegrass [ Poa annua f. reptans (Hausskn.) T. Koyama] and creeping bentgrass ( Agrostis stolonifera L. cv. Penncross) under ice cover maintained for various periods of time under laboratory and field conditions. In the lab, cold‐hardened plants of both species were subjected to either snow‐covered, ice‐covered, or ice‐encased treatments and tested for cold‐hardiness levels at various periods of time. Ice‐encased annual bluegrass plants stored for 90 d were dead, while ice‐covered and snow‐covered plants had cold‐hardiness levels of −4°C and −18°C, respectively. In contrast, at 150 days after treatment (DAT), creeping bentgrass that was ice encased had a cold‐hardiness level of −18°C, while snow‐covered plants had a cold‐hardiness level of −27°C. In the field, annual bluegrass and creeping bentgrass plants were subjected to the following treatments: snow cover, ice cover, and snow or ice removed 45 DAT and then were sampled at various times to determine cold‐hardiness levels. As in the lab, ice cover had less impact on bentgrass than annual bluegrass. At 90 DAT, ice‐covered creeping bentgrass had cold‐hardiness levels of −29°C while annual bluegrass plants were dead at 75 DAT. Snow‐covered annual bluegrass plants still had cold‐hardiness levels of −16°C at 75 DAT. Removing the snow or ice after 45 DAT had little or no effect.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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