Genetic potentials of wheat flour RVA pasting characteristics and cluster analysis
Bibliographic record
Abstract
Seven RVA (Rapid Visco-Analyser) parameters of eighty-four wheat varieties (lines) were analyzed, the results showed: different varieties (lines) possessed significantly different RVA paste visco-properties; all the RVA paste visco-properties had high broad heretability; eighty0four varieties (lines) were clustered into three characteristically different groups based on seven RVA parameters, which had the similar clustering results if based on only peak viscosity, trough viscosity and final viscosity of them. Those varieties (lines) which had similar ecological origins clustered, that is, the majority of varieties from southern areas gathered, which exhibited higher RVA parameters and lower coefficients of variation, and mot of varieties from northern areas and Canada had similar tendency, but they were characteristics of lower RVA parameters and higher coefficients of variation. The rest flocked together, which showed the lowest RVA parameters and highest coefficients of variation, and in this group, final viscosity was higher than or close to peak viscosity. The RVA paste visco-properties of three different groups had the following tendency: Group I (mainly from southern areas)>Group II (mainly from northern areas)>Group III (special group).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".