The ecology of oceanic dispersal and survival of anguillid leptocephali
Bibliographic record
Abstract
Recruitment declines of anguillid eels are difficult to understand because both anthropogenic impacts on juveniles and adults and oceanic changes affecting larval survival or dispersal may be contributing. Anguillid larvae may passively disperse widely from offshore spawning areas but late-stage larvae or glass eels apparently must swim directionally to reach recruitment habitats. Their long larval durations vary among tropical (∼3–4 months) and temperate species (5 months to >1 year). The bodies of anguillid leptocephali are filled with transparent gelatinous material, possibly reducing predation rates and providing an energy reserve for swimming and metamorphosis. Leptocephali feed on marine snow making their first-feeding success linked to primary producers contributing to marine snow production. Alternations between ubiquitous cyanobacteria dominating in low-nutrient conditions and eukaryotic phytoplankton such as diatoms that are important for marine snow production dominating in high-nutrient conditions may influence early-larval survival at first-feeding due to many eggs simultaneously hatching within sympatric spawning areas. Fewer spawning eels resulting from population reductions and variations in early-larval survival may offer some explanations for lower and fluctuating recruitment in recent decades.
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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 | 0.001 |
| 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".