Bibliographic record
Abstract
Research Highlight: McIntosh, A. R., Greig, H. S., & Howard, S. (2022). Regulation of open populations of a stream insect through larval density dependence. Journal of Animal Ecology. https://doi.org/10.1111/1365-2656.13696. Despite decades of research on population regulation through density dependence, it remains challenging to identify and understand the relative importance of mechanisms governing open populations of organisms with complex life cycles. McIntosh et al. (2022) manipulated density of aquatic invertebrates in the field, and then followed populations for 2 years to track the effects on abundance through multiple life-history stages. The authors found that their density manipulation, performed on larvae that were about to pupate, had minimal effects on the number of emergent adults collected several months later. The manipulation had a similarly negligible influence on the number of egg masses laid at study locations. The authors attribute this to stochasticity around dispersal of flying adults through the terrestrial environment. However, later in the study, the authors found evidence of density-dependent population regulation among larval stages, seemingly controlled by resource availability. These results suggest that population dynamics depend on multiple mechanisms operating at different points in organisms' life history, which could either help or hinder population persistence with disturbance or environmental change.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".