1 Farmers and Consultants Receive Training in Spatial Analysis of Yield Monitor Data
Why this work is in the frame
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Bibliographic record
Abstract
In response to suggestions from farmers and agribusiness, Purdue University offered a one-day workshop on spatial analysis of yield monitor data on March 1, 2007. There were 19 participants that included farmers from Indiana, Illinois, and Ontario, and representatives from agricultural input suppliers, farm cooperatives, and private consultants. The workshop was led by Terry Griffin, former Purdue University graduate student and currently Assistant Professor of Agricultural Economics and Agribusiness with the University of Arkansas Cooperative Extension Service. The discussions focused on strategies to design and implement on-farm experiments, collect data and harvest experiments, yield monitor calibration, precision agriculture, and spatial statistical analysis software. “Spatial analysis techniques recently adapted from other disciplines allow farmers and consultants to make better decisions based on their field-scale on-farm trial data collected with yield monitors than previously possible, ” Griffin said. “This workshop serves in part as a pilot program to pass the techniques developed from recent research over to the end users along with some basic statistical training. ” The agenda was largely set by the farmer-collaborators from
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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