Filtração de partículas através do dossel de uma floresta tropical úmida
Bibliographic record
Abstract
Understanding the dinamics of filtration of pollen and spores by plant canopies is crucial to the in the modelling of their dispersal, yet few studies have quantified filtration. Here, we examine the decline in the density of flour particles descending through a 40 m-tall tropical canopy on a windless day at Caxiuanã National Forest, Pará, Brazil. Using these data and estimates of canopy leaf density, we also tested one of the few existing models for the effect of impaction. The Bache model, which incorporates particle and vegetation structure, probability of particle transmission and the probability of impaction, explained approximately 93% of the variation in flour granules captured on passive samplers placed throughout the canopy. The canopy filtered 99.65% of the flour released, but a significant amount of small particles were captured at the forest floor. These findings suggest that the rarity of anemophily seen in the tropics may be more a result of high species richness than high canopy density.
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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 | 0.000 | 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".