Artificial neural networks and genetic dissimilarity among saladette type dwarf tomato plant populations
Bibliographic record
Abstract
Studies have shown that dwarf plants have the potential for use in obtaining hybrids. The aim of this study was to evaluate the agronomic potential and genetic dissimilarity of saladette type dwarf tomato plant populations through the use of artificial neural networks (ANNs). The following traits were analyzed: mean fruit weight, transverse and longitudinal fruit diameter, fruit shape, pulp thickness, locule number, internode length, soluble solids content, and β-carotene, lycopene, and leaf zingiberene contents. A dendrogram obtained by the unweighted pair-group method with arithmetic mean (UPGMA) and Kohonen self-organizing maps (SOM) agreed in the distinction of the BC1F3 populations from the dwarf donor parent. SOM was more consistent in identifying the genetic similarities among the BC1F3 dwarf tomato plant populations and allowed for the determination of weights of each variable in the cluster formation. The UFU SDi 13-1 BC1F3 population was revealed to be a promising option for obtaining saladette type dwarf tomato plant lines.
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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 | 0.000 | 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 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".