Report of the Workshop on Fisheries Management in Marine Protected Areas (WKFMMPA)
Bibliographic record
Abstract
The Workshop on Fisheries Management in Marine Protected Areas [WKFMMPA] (Chair: Jake Rice, Canada) will meet at the ICES Headquarters, Copenhagen, Denmark, from 10–12 April 2007 to:a) Review and discuss results of analysing international fishing activities, fishing efforts in and around the ten designated Natura 2000 sites in the German EEZ. Review the EMPAS interim project report sent to all participants prior to the workshop.b) Review and discuss the objectives/targets for species and habitats in each of the ten Natura 2000 sites in the German EEZ. Specify possible operational objectives to be included in a fisheries management plan.c) From a) and b), identify potential conflicts between fisheries and nature conservation objectives in and around these sites.d) Develop monitoring strategies and guidelines to provide information about the key aspects of fisheries operations identified in a), progress towards conservation objectives in b), and potential conflicts in c).e) Review fishermen information and industry interests to be considered in fisheries management plans in the Natura 2000 sites.f) Review socio-economic aspects to be considered in fisheries management plans in the Natura 2000 sites.g) Review national/international knowledge/experiences with the integration of scientific studies, monitoring, and fishermen information/knowledge.h) Based on e)–g), develop proposals for managing fisheries in the German Natura 2000 sites, including consideration of co-management systems appropriate for management within an ecosystem approach.
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 | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.048 | 0.021 |
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".