An Interactive Online Database for Potato Varieties Evaluated in the Eastern United States
Bibliographic record
Abstract
Databases are commonly used to coordinate and summarize research from multiple projects. The potato ( Solanum tuberosum ) research community has invested significant resources in collecting data from multiple states and provinces, and we have developed a web-based database format for the use of researchers, farmers, and consumers. The northeast regional potato variety development project (NE1031) is a U.S. Department of Agriculture, Cooperative State Research, Education, and Extension Service (USDA-CSREES) regional project focused on developing and evaluating the suitability of new varieties and advanced clones from multiple breeding programs for a range of environments. This multistate project and its predecessors have been in existence for more than two decades, and they have resulted in the collection of a significant amount of standardized potato trial data. We have developed an interactive potato variety database that allows researchers and end-users to access and obtain potato variety trial results in one centralized site. The database is populated with the results of potato variety trials conducted in eight states (Florida, Maine, New Jersey, New York, North Carolina, Ohio, Pennsylvania, and Virginia) and two Canadian provinces (Prince Edward Island and Quebec). It currently contains over 35 data features and was developed primarily for scientists interested in potato variety development, growers, and allied industry members. Hypertext mark-up language (HTML) and hypertext preprocessor (PHP) were used to develop the database interface.
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 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".