Evaluation of Seashore Paspalum in Southeastern Virginia
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
Seashore paspalum (Paspalum vaginatum Sw.) has been successfully grown in warm, humid environments in both the United States and southeastern Asia. In the U.S., seashore paspalum has been planted in parts of North Carolina south to Florida, Texas, California and Hawaii. Very tolerant of low mowing heights, this species has been used primarily for golf courses, but also has applicability as a turf for lawns. High salt tolerance makes it a promising turf for areas near the Chesapeake Bay and the Atlantic Ocean. Research and testing of seashore paspalum in the U.S. has been conducted primarily in Georgia and Florida. Virginia Tech has not conducted any research on this potential new turf species for Virginia. For this project, I have evaluated the adaptability of nine vegetative and three seeded cultivars of seashore paspalum in southeastern Virginia in comparison to Bermuda grass (Cynodon dactylon L.) as an industry standard for comparison. Evaluations of turf cover were made weekly during establishment and at time of spring green-up. Weed competition significantly reduced establishment, with only the vegetative cultivars ‘Sea Star’ and ‘Sea Isle Supreme’ seashore paspalum achieving greater than 65% cover during the first growing season. No cultivar planted by seed successfully established due to weed competition. All seashore paspalum cultivars planted vegetatively survived the winter; however, only Sea Isle Supreme and Sea Star had exceeded 75% turf cover by June 19, 2014, approximately 75 days after breaking dormancy. ‘Yukon’ Bermuda grass achieved an 85% turf cover in the same time frame.
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 | 0.002 | 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 | 0.000 | 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