Connectivity of Greenland halibut in the northwestern Atlantic Ocean inferred from otolith chemistry
Bibliographic record
Abstract
Greenland Halibut (Reinhardtius hippoglossoides) is a deepwater flatfish having a circumpolar distribution. Understanding the spatial connectivity and migratory patterns of this commercially valuable species is essential for ensuring a sustainable fishery; nonetheless, this information remains relatively scarce for many Greenland Halibut populations. Here we evaluate the connectivity and the population structure of halibut along coastal Greenland and Canada to better characterize the contribution of each production zone to the various stocks found in the northwestern Atlantic Ocean. In 2014 and 2016, we sampled 411 large Greenland Halibut from coastal Nunavut, Labrador, and Greenland. We used the elemental fingerprint (magnesium, strontium, and barium) from the otolith core and margin of the sampled fish to determine spatial differentiation of the source areas of the collected halibut. From the 17 sample sites, margin elemental fingerprint delineated four “elemental sectors”, representing pooled adjacent sites having similar chemistry. Overall, 62% of Greenland Halibut were correctly assigned to their sampled coast. Elemental fingerprint of the otolith cores indicated three chemically distinct natal sources for the captured halibut. The chemical record in the otolith cores suggested a high connectivity of Greenland Halibut in the northwestern Atlantic and a main natal source located potentially along the west coast of Greenland. Given that our results suggest the presence of a large nursery around Disko Bay–Hellefiske Bank, protection measures should be considered for this area.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".