Relationship of beet curly top foliage ratings to sugar beet yield
Bibliographic record
Abstract
Sugar beet (Beta vulgaris) varieties were evaluated for disease resistance to curly top to establish\nif disease ratings made in inoculated nurseries correlated with disease ratings and yield in sugar\nbeet crops exposed to natural disease outbreaks. Cultivars were planted both in inoculated curly\ntop nurseries in Kimberly, ID, and in commercial cultivar trials in irrigated fields near Ontario,\nOR and Nampa, ID. Plants were evaluated for curly top using a rating scale of 0 (no symptoms)\nto 9 (dead). Moderate disease pressure in the Ontario (mean rating = 3.8) and Nampa (mean\nrating = 4.1) fields resulted in significant differences for disease rating, root yield, sugar content,\nand estimated recoverable sugar among cultivars. Disease ratings from both commercial fields\nwere positively correlated (r = 0.91 and 0.82, P < 0.0001) with ratings from the inoculated nurseries.\nIn commercial fields, root yield was negatively related to disease rating (r2 = 0.47 and\n0.39, P ? 0.0004). For each unit increase in disease rating (increasing susceptibility), root yield\ndecreased 5.76 to 6.93 t/ha. Thus, curly top nurseries reliably predict curly top resistant cultivars\nfor commercial cultivation
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".