Bibliographic record
Abstract
Abstract Biogeography focuses on the distribution of life forms over the world. Tiger beetles are not evenly distributed across the United States and Canada (fig. 8.1). Range maps for tiger beetles in the United States and Canada show that no two species have exactly the same geographical distribution. On the contrary, each species has a distinctive range, whether measured in total area, shape of the boundaries, or latitudes and altitudes. As with almost all other groups of animals and plants, more species of tiger beetles occur in some parts of the continent than in others. Why should this be? One answer involves historical movements of tiger beetle populations. The evidence for long-range movements of tiger beetles in North America is limited to a few anecdotal examples. Adults in more or less continuous habitats like rivers and ocean beaches have obvious routes of dispersal. However, movements of other species over discontinuous habitats are known. Strong favorable winds are likely involved with the dispersal of species like the S-banded Tiger Beetle, which lives on the muddy tidal flats of the Gulf of Mexico and the west and east coasts of North America. Specimens of this species have been found as far inland as Kansas and on offshore oil platforms in the Gulf of Mexico, 160 kilometers from the nearest land. However, this species has not established a population anywhere in inland North America, but these long-range movements may explain why it occurs on virtually every island in the Caribbean.
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 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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.092 | 0.008 |
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".