Measuring genome size of desert plants using dry seeds
Bibliographic record
Abstract
Use of seeds instead of leaves for the flow cytometric measurement of DNA content is of particular interest to botanists and plant ecologists, since it allows estimation of genome sizes for species having reduced leaves or that accumulate staining inhibitors within leaves, and also for species growing in regions where cytometers are not readily available. The seeds of 24 desert species, including wildflowers, cacti, shrubs, and trees were analyzed by flow cytometry. Nuclei were used from either total seeds or seed tissues, following dissection to determine the seed parts that were most suitable for genome size measurement. In addition, the mass of 100 seeds was established. The seeds of 14 species contained only cells occupying a mitotic cell cycle. For 10 other species, endoreplicated nuclei (up to 32C) were detected. Using entire seeds or their parts, it was possible to estimate genome sizes for all of the species, which ranged from 0.79 pg per 2C in Parkinsonia aculeata L. to 26.96 pg per 2C in Agave parryi Engelm., thus this kind of plant material can be used for the cytometric measuring of nuclear DNA content. However, a detailed understanding of seed biology is needed to interpret the results correctly. The relationships among genome size, seed mass, and desert growing conditions are also discussed.
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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) | 0.000 | 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 | 0.000 |
| 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".