A simple, non‐toxic method for separating seeds based on density, and its application in isolating <i>Arabidopsis thaliana</i> seed oil mutants
Bibliographic record
Abstract
Premise Seed oil is an economically important trait in Brassica oilseed crops. A novel method was developed to isolate Arabidopsis thaliana seeds with altered oil content. Methods and Results In A. thaliana, seed oil content is correlated with seed density, with high‐oil seeds being less dense than wild type and tending to float in solution, and low‐oil seeds being denser and tending to sink. In contrast to previous methods, which used toxic chemicals and density gradient centrifugation, different concentrations of calcium chloride (CaCl2) were employed to separate seeds without the need for centrifugation. The method was validated using known seed oil mutants, and 120,822 T‐DNA mutagenized A. thaliana lines were then screened for novel seed density phenotypes. Conclusions A number of candidate mutants, as well as new alleles of two genes known to influence seed oil biosynthesis, were successfully isolated.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".