Genetic and environmental variation in alfalfa forage yield from variety testing experiments conducted in North America between 1986 to 1999 (Version 2)
Bibliographic record
Abstract
The yield dataset contains forage yield data from over 700 alfalfa variety tests conducted by researchers in the US and Canada from 1986 through 1999. Some trials also measured forage quality and stand; these data are also available in PURR. The data were aggregated from the Alfalfa Variety Performance Database originally compiled in 2000 by Daniel W. Wiersma and Wayne G. Hartman (doi: 10.4231/PHKH-4334). The database was used to analyze long-term trends in genetic improvement of alfalfa yield and agronomic performance across a broad range of environments. The yield file contains cultivar-specific yield data for each harvest within a year. It is organized by Trial, and includes trial-specific spatial (state, latitude, longitude, elevation), and temporal (year of trial, harvest number, harvest date, planting date) details. Finally, when available soil type and statistics are also provided. A companion dataset in PURR contains the characteristics of these alfalfa varieties (doi: 10.4231/FMY9-6966).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
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 source (direct Gemma or distilled Codex), 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".