Soybean seed quality and early development in cold climate conditions
Bibliographic record
Abstract
Soybean [Glycine max.(L.) Merr.] development is constrained by suboptimal growing conditions during germination and emergence.In cold climate regions, biostimulants could enhance the cold tolerance of developing soybeans, as well as the quality and viability of the next generation (F2) of soybean seed.The objectives of this thesis were to determine if the F2 seed of soybean had i) better quality based on seed protein and mineral nutrient content, and ii) greater cold tolerance during germination and emergence when the parent (F1) generation was treated with biostimulant, namely two formulations provided by Via Végétale.I hypothesised that F2 seed will have higher concentrations of proteins, such as 7S and 11S, and mineral nutrients, such as K, Ca, and Mg, when the F1 parent generation was treated with biostimulant, compared to no biostimulant treatment.Furthermore, I hypothesised that F2
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".