2014 Kansas Performance Tests with Corn Hybrids
Bibliographic record
Abstract
Corn performance tests, conducted annually by the Kansas Agricultural Experiment Station, provide farmers, extension workers, and seed industry personnel with unbiased agronomic information on many of the corn hybrids marketed in the state. Because entry selection and location are voluntary, not all hybrids grown in the state are included in tests, and the same group of hybrids is not grown uniformly at all test locations. \nContributors \nMain Station, Manhattan \nJane Lingenfelser, Assistant Agronomist (Senior Author) \nDoug Jardine, Extension Plant Pathologist \nJeff Whitworth, Extension Entomologist \nMary Knapp, KSU Weather Data Librarian \nEdward O. Quigley, Agricultural Technician \nExperiment Fields \nEric Adee, Topeka \nGary Cramer, Hutchinson \nJames Kimball, Ottawa \nMichael Larson, Scandia \nWendell Lilyhorn, Hutchinson \nRandall Nelson, Scandia \nKeith Thompson, Hutchinson \nResearch Centers \nWayne Aschwege, Hays \nDeWayne Bond, Tribune \nPatrick Evans, Colby \nKelly Kusel, Parsons \nAlan Schlegel, Tribune \nMonty Spangler, Garden City \nCooperators \nGene Eidman, Strong City \nFuhrman Farms, Severance \nLance Rezac, Onaga \nNorman Schmidt, Inman \nClayton Short, Assaria \nJustin Vosburgh, Macksville
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".