Male reproductive success is not strongly affected by phenological changes in mate availability in monoecious <i>Sagittaria latifolia</i>
Bibliographic record
Abstract
Many plants express their female and male sex roles at different times (dichogamy), with important consequences for mating. Dichogamy can yield mate limitation via biased floral sex ratios, particularly at the beginning and end of the flowering season when many plants simultaneously function as the same sex. This form of mate limitation should be reduced if plants adjust their allocations to female versus male sex functions in a manner that tracks seasonal variability in mating opportunities. For example, under protogyny (i.e. dichogamy with female function expressed first) plants with male-biased sex expression should have enhanced mating opportunities early in the flowering season as other plants begin to flower (in female sex phase). We quantified seasonal changes in sex allocation, patterns of mate availability and realized siring success in a population of protogynous Sagittaria latifolia . Our results were consistent with previous findings that seasonal changes in sex allocation should compensate for lost mating opportunities under the temporally variable mating environments caused by dichogamy. However, patterns of siring success in the population were inconsistent with this interpretation. We suggest that realized siring success might depend more strongly on spatial than on temporal aspects of mate availability.
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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 | 0.000 | 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".