Bibliographic record
Abstract
Abstract Populations are collections of individuals of the same species that occupy a defined place (Krebs 2001). In sexually reproducing species, they can vary in size from a single pair of breeders on an island to billions of migratory locusts. Some populations, like locusts, are highly mobile and extend over vast areas. Others live discontinuously in patchy habitats, on mountaintops, or on island archipelagoes. Collections of subpopulations are sometimes termed metapopul.ations (Hanski 1999), where movements of individuals link the dynamics of adjacent subpopulations. All populations fluctuate, growing when reproduction and immigration exceed mortality and emigration, and declining when the reverse conditions apply. When numbers fluctuate in a large population, local extinction (hereafter extirpation) is unlikely, because it is likely that some individuals will survive even the harshest conditions. However, fluctuations can cause small populations to disappear or decline to a size where genetic decay or random loss become likely. If only one population of the species remains, global extinction can follow. The behavior of small and isolated populations is thus of central interest to conservation biologists whose aim is to save rare and declining populations. In this book, we examine how small size influences the genetic structure and ecological performance of populations. In particular, we use a 28-year study of a small songbird, the song sparrow, on a tiny island in western Canada to illustrate the effects of chance processes on the ecology and genetic composition of the population.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".