Associations between flatfish abundance and surficial sediments in the eastern Bering Sea
Bibliographic record
Abstract
Spatially explicit relationships between pleuronectid flatfish abundance and surficial sediments in the eastern Bering Sea were investigated using published sediment descriptions and trawl survey data (1982-1994). Flatfish food habits were also examined because sediment properties are known to affect the distribution and abundance of benthic prey. For six species, we compared sediment textures in areas of highest and lowest abundance (kilograms per hectare). Sand predominated in areas of high yellowfin sole (Pleuronectes asper) (YFS) (p << 0.001) and rock sole (Lepidopsetta spp.) (RS) (p << 0.001) abundance, while mixed sand and mud was most common in areas of lowest abundance. In contrast, mixed sand and mud predominated in areas preferred by flathead sole (Hippoglossoides elassodon) (FHS) (p << 0.001), Alaska plaice (Pleuronectes quadrituberculatus) (AP) (p = 0.002), and arrowtooth flounder (Atheresthes stomias) (ATF) (p = 0.004), with more diverse substrates in low-density areas. Areas of high and low Greenland turbot (Reinhardtius hippoglossoides) (GT) (p = 0.845) abundance had similar sediment textures (primarily mixed sand and mud). Species with highly restricted diets (AP) or piscivores with weak sediment associations (GT, ATF) had relatively inflexible food habits, whereas YFS, RS, and FHS food habits varied considerably with sediment type. Our findings suggest that benthic-feeding pleuronectids prefer certain sediment textures because of adaptive differences in prey availability.
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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 | 0.001 |
| 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".