Changes in distribution of Greenland halibut in a varying environment
Bibliographic record
Abstract
Abstract Morgan, M. J., Garabana, D., Rideout, R. M., Román, E., Pérez-Rodriguez, A. and Saborido-Rey, F. 2013. Changes in distribution of Greenland halibut in a varying environment. – ICES Journal of Marine Science, 70: 352–361. Fish are expected to respond to changing oceanographic temperature by altering their distribution. Off the coast of Newfoundland, Canada, there have been major changes in oceanographic temperature over the last several decades, with both record cold and record warm years being observed. Greenland halibut is an important flatfish species in the area, and is distributed in deep waters over a very wide geographic range. Thus, it might be buffered from temperature change in the overall area by reduced temperature variation at depth, and the diverse temperature conditions over its wide range. We examined intrapopulation variation in temperature and depth distribution, and the biological changes in relation to changes in available temperature. On the Flemish Cap, variation in available temperature was limited, and changes in depth were related to changing age composition and the differential depth distribution with age/size. In other areas there was a larger decline in available temperature, and associated with this, Greenland halibut moved to deeper waters and occupied warmer temperatures than they had previously. Concurrently, growth declined and condition increased. This study shows that shifts in distribution may not result in maintenance of homogeneous environmental conditions, and that resulting biological changes will be difficult to predict.
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 | 0.001 |
| 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".