Growth–feeding linkage in small pelagic fish larvae in the Kii Channel, Japan
Bibliographic record
Abstract
Abstract The linkage between growth rate and feeding success has been shown to strengthen the effects of early growth rate on later growth rate in the early life history of fish. However, the growth–feeding linkage largely remains to be tested at the individual level within the same populations/cohorts. We examined the growth–feeding linkage for multiple populations/cohorts in Japanese anchovy Engraulis japonicus larvae and Pacific round herring Etrumeus micropus larvae, through otolith microstructure analysis, based on samples collected from the commercial fishery for larval fish in the Kii Channel, Japan. The three growth–feeding mechanisms, which are based on the respective potential advantages of larger somatic size, higher growth rate, and earlier morphological development for achieving feeding success, were tested to understand how growth rate relates to feeding success. The “somatic size” mechanism was supported for all of six samples for anchovy larvae and three of four samples for round herring larvae. The “growth rate” mechanism was supported for two of six samples for anchovy larvae and three of four samples for round herring larvae. The “morphological development” mechanism was supported for three of four samples for anchovy larvae and all of three samples for round herring larvae. Overall, the present analysis supported the growth–feeding linkage but revealed the dynamics of the growth–feeding mechanisms. All the mechanisms were shown to operate at least for certain populations/cohorts, but none of them were universally effective over all populations/cohorts across the two species. Understanding the dynamics of the growth–feeding mechanisms would provide precious hints for considering strategies of predicting recruitment dynamics.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".