Acorn production by Kashiwa oak in a coastal forest under fluctuating weather conditions
Bibliographic record
Abstract
We modeled the annual acorn crops of Kashiwa oak (Quercus dentata Thunb.) in a coastal forest in Hokkaido, northern Japan. Shoots of Kashiwa oak withered away during winter because of sea breeze and cold, and succeeding production of female inflorescences were strongly affected by mortality of buds. Thus, strong sea breeze and cold winters reduced the survival ratio of buds and further resulted in reduction of female flowering. Number of female flowers was related with current acorn crops, however, survival of female flowers after pollination was strongly influenced by warmth in the flowering period. Regression analysis of the annual acorn crop versus weather conditions suggests that acorn crop was decreased by cool conditions in the flowering period. A model equation was constructed to estimate the annual acorn crops by three weather variables: cumulative velocity of sea breeze and mean monthly temperature in winter (DecemberMarch) and maximum monthly temperature in current flowering period (June). This model equation explained 89.2% of observed acorn crops of Kashiwa oak in the coastal forest.
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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) | 0.000 | 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".