Bibliographic record
Abstract
It has become clear that long-distance seed dispersal plays a crucial role in plant metapopulation persistence and response to rapid climate change. Recent studies of the role of convective vs. shear-generated updrafts in prompting long-distance dispersal using Taraxacum officinale as an example, suggest that (1) the probability of abscission is independent of horizontal speed and thus (2) shear-induced vertical turbulence is low, and so by default the bulk of updrafts must be due to convection, especially in open habitats such as grasslands. In this paper, I directly test the first hypothesis, and indirectly test the second via a modeling exercise. Employing shorter averaging times than used previously, it is shown that abscission in T. officinale is controlled by horizontal wind speed. Indeed, it is related to the square of the wind speed, as might be expected if drag is the motive force. I also show that this augmentation of wind speed by the abscission bias should sufficiently increase the shear-induced turbulence so that shear rivals convection as a source of updrafts in open habitats. In conclusion, long-distance dispersal by wind will not be successfully modeled until we couple the abscission and subsequent dispersal processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".