Year-round monitoring of Arctic species of sculpin to identify residency and seasonality of movement behavior
Bibliographic record
Abstract
Environments change across space and time, often requiring organisms to exhibit behavioral responses. In the Arctic, migratory consumers are motivated by spring resources to follow receding ice; however, resident species’ responses to this ephemeral productivity are less well understood. We characterized the movement behaviors of relatively sedentary Arctic species of sculpin ( Myoxocephalus spp.) in Tremblay Sound, Nunavut, Canada. Movements of individuals ( n = 60) captured during the ice-free periods of 2017–2019 were monitored year-round via an array of acoustic telemetry receivers ( n = 37). Telemetry data confirmed year-round residency within the Sound, yet sculpins were consistently more active and wider ranging during the ice-free period versus the ice-covered winters. Sequence analysis revealed distinct patterns of activity differentiated primarily by regional associations. Together, these results indicate sculpins are highly sedentary, but move more during the ice-free season, suggesting the importance of the seasonal productivity pulse to these fishes. As resident species are adapted to exploit the conditions within their local environment, sculpins provide valuable indicator species to monitor coastal and benthic Arctic ecosystems that are experiencing rapid change.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".