Seasonal changes in depth distribution of salmon sharks (<i>Lamna ditropis</i>) in Alaskan waters: implications for foraging ecology
Bibliographic record
Abstract
The salmon shark, Lamna ditropis, is an endothermic, apex predator in the productive waters of the Gulf of Alaska (GOA). To understand their role in these productive habitats and to identify and better understand their interactions with commercially important species and fisheries, detailed information regarding the distribution of the salmon shark is required. Archival data records from eight recovered pop-up archival transmitting (PAT) tags were analyzed to examine the geographic and vertical distribution of female salmon sharks and elucidate how their distribution changes in relation to the biotic and abiotic environment. Tagged sharks used the neritic habitats of the GOA for the duration of the PAT deployments. Sharks exhibited a diel periodicity in their dive behavior. Salmon sharks exhibited three different patterns of depth distribution (behavioral modes) that occurred during distinct oceanographic seasons, likely reflecting changes in their foraging ecology in response to seasonal changes in the distribution and availability of important prey. The distribution of salmon sharks in the GOA appears to follow consistent patterns and has a high degree of geographical and vertical overlap with commercially important prey species. This information increases our understanding of interactions between salmon sharks and commercial fisheries and may assist in fostering responsible management for this species.
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 | 0.000 | 0.000 |
| 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".