The University of Tennessee Gardens and Herbaceous Plant Evaluation Program
Bibliographic record
Abstract
Many new plants and varieties are introduced into the market every year. Little information is generally available about the landscape performance of these plants. To take the guesswork out of their landscape performance in the Tennessee region, the Univ. of Tennessee Institute of Agriculture (UTIA) Gardens were established. Started in 1983 as an All-America Selections (AAS) Test Garden, on less than a quarter of an acre, the UTIA Gardens have grown to 5 acres and now include plant introductions from 25 commercial seed and plant companies. An average of 550 summer and winter annuals are evaluated annually in addition to an assortment of bulbs, perennials, herbs, groundcovers, ornamental grasses, aquatics, trees, and shrubs. Because of the volume of plants, evaluation criteria are in conjunction with industry requests and are not always replicated. In addition to university support, the gardens receive revenues from the sponsoring commercial seed and plant companies, the Tennessee green industry trade associations, a “Friends of the Gardens” support group, and gifts. As a result of the herbaceous plant evaluation program, the UTIA Gardens have grown to be a significant resource for the university, community, and green industry. A variety of university departments use the gardens in their teaching; community groups, including schools, tour and use the gardens; and open houses and field days assist commercial growers and landscapers in remaining current on new plant introductions and their performance.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.061 | 0.006 |
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".