The abundance of juvenile yellowtail (<i>Seriola quinqueradiata</i>) near the Kuroshio: the roles of drifting seaweed and regional hydrography
Bibliographic record
Abstract
Abstract We assess the effect of drifting seaweed (Sargassum sp.) biomass, geography and hydrography on juvenile yellowtail (Seriola quinqueradiata) abundance variation off the southeast coast of Japan, near the Kuroshio Current. The amount of drifting seaweed mats progressively increased northeastward into the cooler, coastal waters. Frontal structure indexed using a station‐to‐station ΔSST did not explain spatial variation in the seaweed mat distribution, although the western extent of the Kuroshio Current appeared to act as a boundary. Juvenile yellowtail constituted 51–62% of the fish collected in association with drifting seaweed mats in April 1996 and 1997 and 29% in June 1996. The abundance of juvenile yellowtail was positively correlated with seaweed biomass. The geographic distribution of juvenile yellowtail associated with drifting mats varied among sampling periods, being more southwesterly in April and more northeasterly in June. Simple multiple regression models based on seaweed biomass and geographic distribution (latitude) explained between 35% and 43% of the variation in juvenile yellowtail abundance in spring. Associations with spatial and temporal variations in hydrographic conditions did not contribute to explained variation in a meaningful manner. The results presented here indicate that, off the southeast coast of Japan during April, yellowtail juveniles are likely to be most abundant when seaweed biomass is high, occur offshore, and are bounded by the western extent of the Kuroshio Current near the 19–20°C SST isotherm.
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 | 0.000 | 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".