The influence of age and cohort on the distribution of walleye pollock (<i>Gadus chalcogrammus</i>) in the eastern Bering Sea
Bibliographic record
Abstract
The spatial distributions of marine fish populations are influenced by environmental conditions, intrinsic properties of the populations, and prior distribution. The influence of these factors may not be consistent across age classes. For this study, age composition estimates for walleye pollock ( Gadus chalcogrammus) collected on bottom-trawl surveys in the Bering Sea were used to estimate range correlation indices, population centers of gravity, and effective area occupied. Age-specific density maps suggested a circular ontogenic migration during the summer feeding season, with the youngest and oldest groups most broadly distributed. Range correlation analysis among age groups and year classes provided clear evidence of a population cohort effect in the spatial distribution of the population. Variance decomposition analysis indicated that the variance in the spatial distribution of age groups during summer was influenced by the initial distribution of that cohort as recruits. Model-based analyses showed that extrinsic temperature variables affected the youngest and oldest age classes the most, but provided no indication of age-related effects for intrinsic population factors. This study showed that both cohort and age-specific factors are important drivers of spatial distribution.
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 | 0.001 | 0.002 |
| 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".