Weather-related patterns of fruit abscission mask patterns of frugivory
Bibliographic record
Abstract
Previous studies on frugivory in temperate bird-dispersed plants have concluded that fleshy fruits are removed more rapidly in cold than in warm winters. However, these studies do not distinguish between fruit abscission and frugivory. The implicit assumption that fruit loss reflects frugivory may not be valid; fruit abscission may be important and respond differently to weather. During two winters, we measured fruit loss from an invasive shrub ( Lonicera maackii (Rupr.) Herder) using fruit traps. We examined the effects of temperature and precipitation on fruit retention on shrubs and fruit abscission. In the first year of our study, there was no effect of temperature or precipitation on fruit retention. In the second year, both warmer temperatures and lower precipitation resulted in more fruit retention. In both years, fruit abscission was greater during periods of cold temperatures and high precipitation. These findings suggest that weather-dependent “frugivory” reported for other bird-dispersed plants may actually reflect patterns of abscission.
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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) | 0.001 | 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".