Bibliographic record
Abstract
Many of the leading ecological and evolutionary characteristics of populations are governed by their effective population size, which in turn is strongly influenced by the minimum census size. The succession of minima of increasing rank R in time is described by the expected value of the next minimum ω R and by the expected time T R elapsing before it occurs. The relationships of ω R and T R with R together determine the minimal population expected to be encountered within a given period of time. These relationships depend on the dynamic model for species abundance. The four main types of model investigated here have characteristically different successions. – Random: ω R log‐linear and T R log‐linear on R; – Forced: ω R linear and T R log‐linear on R; – Neutral community: ω R linear and T R linear on R; – Foodweb: ω R log‐linear and T R linear on R; Data on species abundance in long‐term surveys of plankton communities suggests that the Foodweb model best represents nature. This implies that each species is likely to encounter new minima on time‐scales much shorter than species longevity. Either local selection and dispersal or large population size may help to alleviate frequent bottlenecks, but it is likely that the internal dynamics of trophically structured communities may lead to continual change in species composition.
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) | 0.001 | 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 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".