2009 Kansas performance tests with grain sorghum hybrids
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
Grain Sorghum 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 grain sorghum 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 at all test locations. Contributors: Main Station, Manhattan: Jane Lingenfelser, Assistant Agronomist (Senior Author); Doug Jardine, Extension Plant Pathologist; Mary Knapp, KSU Weather Data Librarian; Edward O. Quigley, Agricultural Technician; Holly Schwarting, Extension Entomologist; Brent Christenson, Agronomy; Alex King, Agronomy; Experiment Fields: Eric Adee, Topeka; Gary Cramer, Hutchinson; Jim Kimball, Ottawa; Michael Larson, Belleville; Wendell Lilyhorn, Hutchinson; Doug Stensaas, Belleville; Keith Thompson, Hutchinson; Research Centers: Patrick Evans, Colby; Lonnie Mengarelli, Parsons; Gerald Rohlder, Hays; Alan Schlegel, Tribune; Monty Spangler, Garden City; Cooperators: Calvin Bohnert, Mankato; Clayton Short, Assaria.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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