History of hydroacoustic surveys of small pelagic fish species in the European Mediterranean Sea
Bibliographic record
Abstract
The study of small pelagic fish by hydroacoustic methods in the Mediterranean Sea began in the Adriatic in the 1950’s. Since 2009, internationally coordinated, extensive, regular surveys have been conducted in the framework of the MEDIAS - Mediterranean International Acoustic Surveys – action, under the EU Data Collection Framework, to provide inputs for the management of small pelagics, particularly European anchovy (Engraulis encrasicolus) and European sardine (Sardina pilchardus). The surveys cover EU Mediterranean waters and monitor the distribution and abundance of small pelagic species using a common protocol. The hydroacoustic surveys, historically conducted by each Country separately, have since been standardized and harmonized. This is a review of the evolution of the surveys from the beginning up to the present and discusses the future prospects. It reports the historical time series of anchovy, sardine and other small pelagics in different areas and describes the spatial and temporal distribution of small pelagic species in decadal maps of the major areas of their distribution in the European Mediterranean Sea. Furthermore, it discusses the use of MEDIAS data for stock assessment purposes, the collection of auxiliary information for an ecosystem-based management approach, the need for further standardization and future challenges.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".