Bibliographic record
Abstract
Bermudagrass (Cynodon dactylon (L.) Pers.) is a perennial warm-season turfgrass that is widely used in the central and southern part of the United States. The drought performance of 67 experimental selections made from the normally seed-propagated cultivars 'Yukon', 'Riviera' and ' OKS 2004-2' bermudagrass, with two cultivars `Celebration' and `Premier' serving as standards. Field research plots were established at the Oklahoma State University Turfgrass Research Center in Stillwater, OK in 2012 in a randomized complete block design with four replications. Plots were evaluated in the field during and following a one month drought treatment period in 2012 and 2013. Plots received no water from irrigation or natural rainfall during the treatment period. Right after the drought period, plots were irrigated to allow grass recovery and the recovery rate was measured. Parameters measured included turf quality, leaf firing, normalized difference vegetation index, soil volumetric water content, and digital image analysis. Based on data collected in 2012 and 2013, two experimental genotypes, `1x9' and `20x7', showed significant improvement in field drought performance compared to all other entries and performed better than the highly drought resistant standard Celebration.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".