On‐Farm Strip Trials vs. Replicated Performance Trials for Cultivar Evaluation
Bibliographic record
Abstract
A systematic comparison between two cultivar evaluation and recommendation systems, i.e., the balanced and replicated performance trials conducted in small plots at a small number of locations, and the unbalanced and non‐replicated on‐farm trials conducted in large strips on many farms, is lacking. This study was initiated to investigate the usefulness of the two contrasting systems in cultivar evaluation and the relationships between them. Yield data from Ontario winter wheat ( Triticum aestivum L.) strip trials and performance trials for 1998 to 2000 were analyzed by mixed models. For all 3 yr, results from the two systems were highly correlated, both in terms of the best linear unbiased predictors (BLUP) and for the t ‐values of BLUP. Cultivars judged to be superior (or inferior) by one system were never judged to be inferior (or superior) by the other. Thus, both on‐farm strip trials and replicated small‐plot trials provide valid data for effective cultivar evaluation. On the basis of t ‐statistics, which measure cultivar reliability, cultivars can be classified into superior ( t ≥ 2), inferior ( t ≤ −2), and intermediate or inadequately tested (−2 < t < 2). Two cultivars can be regarded as different in reliability if their t ‐values differ by ≥3. The evaluation power of strip trials for a cultivar depends on the number of trials in which the cultivar is tested; a cultivar may not be adequately evaluated if it is tested in fewer than 20 trials.
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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 | 0.013 | 0.006 |
| 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 | 0.000 | 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 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".