Early selection of full-sib potato families
Bibliographic record
Abstract
Clonal selection is the preferred breeding method used in potatoes (Solanum tuberosum L.). However this selection procedure is only efficient for more advanced generations and shows no good results when applied in the seedling up to the second clonal generation. This study assessed the feasibility of selection in early generations of full-sib potato families and compares the selection method among and within families with the combined selection under different selection intensities. Six experiments were conducted from the first (C1) until the third clonal generation (C3). In C1 a randomized complete block design with four replications of 25 plants was used. In the remaining generations RCB was employed with three replications of 10 plants. Genetic variances were lower between families than within families, for all traits, but the heritabilities between families were almost always larger. The expected gains from selection between and within families were superior to gains from the combined selection in any intensity of selection. The selection of families should have weaker intensity than selection among clones within families. The selection of families was more efficient when based on the average of environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".