Bibliographic record
Abstract
We have constructed a model of community dynamics that is simple enough to enumerate all possible food webs, yet complex enough to represent a wide range of ecological processes. We use the transition matrix to predict the outcome of succession and then investigate how the transition probabilities are governed by resource supply and immigration. Low-input regimes lead to simple communities whereas trophically complex communities develop when there is an adequate supply of both resources and immigrants. Our interpretation of trophic dynamics in complex communities hinges on a new principle of mutual replenishment, defined as the reciprocal alternation of state in a pair of communities linked by the invasion and extinction of a shared species. Such neutral couples are the outcome of succession under local dispersal and imply that food webs will often be made up of suites of trophically equivalent species. When immigrants arrive from an external pool of fixed composition a similar principle predicts a dynamic core of webs constituting a neutral interchange network, although communities may express an extensive range of other webs whose membership is only in part predictable. The food web is not in general predictable from whole-community properties such as productivity or stability, although it may profoundly influence these properties.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".