Temperate fish community variation over seasons in relation to large-scale geographic seascape variables
Bibliographic record
Abstract
In shallow-water marine environments, ecosystem functioning is a complex interworking of fine-scale characteristics and region-wide factors, and the importance of these variables can vary on multiple temporal and spatial scales. This underwater video study targeted seasonal changes in the fish community of seagrass habitats along the Swedish west coast and the influence of offshore seascape variables (latitudinal position, wave exposure, open ocean, and deep water). Results showed that fish assemblage structure exhibited seasonal changes between summer and autumn and strong spatiotemporal variations in the importance of offshore factors affecting shallow-water fish communities. In summer, abundance from the Gobiidae family responded to wave exposure, whereas the Gadidae family and juvenile migrant habitat preference guild responded to latitudinal position and proximity to deep water. In autumn, deep water was related to abundance of Gadidae and juvenile migrants, whereas latitudinal position influenced Gasterosteidae. These findings underscore the importance of understanding the influence of offshore factors on facets of coastal fish assemblages to address large-scale geographic connectivity along nearshore–offshore gradients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".