Methods for characterizing pollen fitness in Cannabis sativa L.
Bibliographic record
Abstract
Pollen grains are male gametophytes, an ephemeral haploid generation of plants, that commonly engage in competition for a limited supply of ovules. Since variation in reproductive capabilities among male gametophytes may influence the direction and pace of evolution in populations, we must be able to quantify the relative fitness of gametophytes from different sires. To explore this, we estimated the relative fitness of groups of male gametophytes in a dioecious, wind-pollinated model system, Cannabis sativa, by characterizing the non-abortion rate (measured via chemical staining) and viability (measured via in vitro germination) of pollen from multiple sires. Pollen viability quickly declined within two weeks of anther dehiscence, and pollen stored under freezer conditions did not germinate regardless of storage time. In contrast, pollen non-abortion rates declined slowly and persisted longer than the lifetime of a sporophyte plant under both room temperature and freezer conditions. Pollen samples that underwent both viability and non-abortion rate analysis displayed no significant correlation, implying that researchers cannot predict pollen viability from non-abortion rates, nor infer male gametophytic fitness from a single measure. Our work demonstrates two independent, differential approaches to measure proxies of male fitness in C. sativa.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".