Testing the environmental prediction hypothesis for mast-seeding in California oaks
Bibliographic record
Abstract
We analyzed 29 years of acorn production by five species of California oaks (genus Quercus ) to test the hypothesis that trees produce large seed crops prior to wet years, conditions facilitating seedling germination and survival. The mean crop of three of the species correlated positively and nontrivially with the following year’s rainfall, but none was statistically significant. Including the acorn crop 1 and 2 years earlier yielded several significant relationships between the acorn crop and future rainfall, but none held up when applied to a second, independent site. Across individuals, acorn production by 7% of trees correlated significantly with subsequent rainfall. Although these trees differed from other trees in several characters, differences were not sufficient to discriminate between trees that correlated significantly with subsequent rainfall from those that did not. We conclude that acorn production by California oaks does not forecast wet years and does not support the environmental prediction hypothesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".