Greenland halibut (Reinhardtius hippoglossoides) spawn annually but successive cohorts of oocytes develop over 2 years, complicating correct assessment of maturity
Bibliographic record
Abstract
Ovary development in Greenland halibut ( Reinhardtius hippoglossoides ) is complex, with several cohorts of developing oocytes present during vitellogenesis; this is unusual for a determinate spawner. There are also speculations that Greenland halibut are not capable of spawning every year. To investigate this possibility, ovaries from Greenland halibut caught throughout the year were examined histologically, and successive cohorts of oocytes were tracked through development. Results showed that the initial maturation of the ovaries from immature to spawning takes more than 1 year. The ovary initially develops as far as early vitellogenesis; however, the time scale for this is unclear. During the final year of development, the cohort of vitellogenic oocytes splits to form two cohorts; the larger cohort increases in size and is spawned in the coming spawning season. The smaller cohort also continues to develop, but at a much lower rate, in preparation for development for spawning in the following year. Within each month, there is a large range of oocyte sizes between fish; this leads to the extended spawning season that is known in many populations of this species. This complicates the assessment of maturity, and a more accurate microscopic maturity scale is proposed.
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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 | 0.000 | 0.000 |
| 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".