A length-based approach to predator–prey relationships in marine predators
Bibliographic record
Abstract
Body size is a critical feature of the ecology of most organisms and has been used to describe and understand predator–prey interactions in both terrestrial and aquatic environments. Most previous studies have used prey mass to examine the relationships between predator size and prey size; however, using prey lengths may provide a different perspective, particularly for gape-limited fishes. Using a large database of predator and prey lengths for marine aquatic predators, I found the expected positive wedge-shaped relationship between predator length and prey length and a negative converging relationship between relative prey length (prey–predator length ratio = a measure of trophic niche breadth) and predator length. Distinct patterns in the size scaling of this measure of trophic niche breadth were identified using quantile regression: converging relationships were common among adults but absent among larvae. This difference suggests contrasting ontogenetic foraging opportunities between adults and larvae: a lack of large relative prey sizes for the largest adult predators, and a greater ability of larvae to include larger prey items in their diet as they grow.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".