Cumulative effects of mortality factors on reproductive output in two co-occurring <i>Quercus</i> species: which mortality factors most strongly reduce reproductive potential?
Bibliographic record
Abstract
We examined the factors that limit the potential reproductive output by two co-occurring deciduous oaks, Quercus variabilis Blume and Quercus serrata Thunb. ex Murray, studied over two growing seasons. We assessed the relative importance of each factor that could affect reproductive potential during the pre-dispersal phase on the basis of both the magnitude of the reproductive loss and the variation in such losses. Five factors (abortion of pistillate flowers, abortion of acorns, predation by an immature acorn-feeding guild of insects, predation by a mature acorn-feeding guild of insects, and degeneration of acorns) reduced the reproductive potential of Q. variabilis during the pre-dispersal phase. Of these factors, insect predation by the immature acorn-feeding guild and by the mature acorn-feeding guild made the greatest contribution to the variation among plants in total reproductive losses, even though they did not always cause the largest overall reproductive losses. For Q. serrata, the same five factors plus predation by a guild of insects that feeds on pistillate flowers affected reproductive potential during the pre-dispersal phase. Of these factors, abortion of pistillate flowers was responsible for the majority of the reproductive losses and made the largest contribution to the variation among plants in overall reproductive losses.
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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 | 0.001 | 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) | 0.000 | 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".