Report of Working Group 24 on Environmental Interactions\nof Marine Aquaculture
Bibliographic record
Abstract
This report is a summary of the activities that WG 24 undertook from 2009 to 2012. The Working Group, with the guidance of FIS and MEQ, refined the activities under the terms of reference so that each PICES member country with active Working Group members could contribute to the report. This refinement was required due to the different types of expertise needed to meet the three very different activities outlined in the terms of reference.Through topic sessions, workshops and targeted Working Group activities, different aspects of sustainable marine aquaculture research relevant to WG 24’s terms of reference were highlighted. Research activities in all PICES member countries focus on identifying aquaculture–environment interactions, whether to model the impacts or to minimize them through optimizing culture approaches, as well as on research related to disease identification and management.Based on the experience of WG 24 and the direction of PICES under its FUTURE science plan, some marine aquaculture issues and analysis can be more holistically addressed through expert groups that include consideration of anthropogenic stressor effects on the marine environment. Additionally, any future marine aquaculture-related PICES expert group should be more narrowly focused to not only allow for more directed work, but also to increase the likelihood of experts from all PICES member countries being able to participate and contribute.This report is composed of three sections: Assessing environmental interactions of marine aquaculture, marine aquaculture legislative frameworks and environmental interactions research, and pathogens of aquatic animals organized as country reports.
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 | 0.017 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.009 |
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".