Report of the Working Group on Integrated Coastal Zone Management (WGICZM)
Bibliographic record
Abstract
The first meeting of the ICES Study Group on Information Needs for Coastal Zone Management (SGINC) was held in Esporles, Mallorca, Spain, 5–7 May 2003 with 15 participants from Canada, Denmark, Norway, Poland, Spain, Sweden, the Netherlands, and the United Kingdom. The Chair, J. Støttrup (Denmark), reviewed the background for the establishment of this Study Group. Many fisheries are dependent on coastal ecosystems, which function as areas for feeding and spawning and as nursery grounds. The production and utilisation of these marine, renewable resources cannot be sustained where the functional integrity of coastal systems is degraded. There is, however, a rapidly growing pressure on the coastal zone and evidence of increasing degradation of coastal waters around the globe due to a wide range of human activities. Examples are habitat alteration, eutrophication, toxic pollution and overfishing. Conservation of healthy and well functioning coastal ecosystems, to provide both goods and services to humanity in the future, calls for new sustainable management strategies. ICES addresses today many of the issues of biodiversity and marine habitat primarily within the realms of the Marine Habitat Committee, but also in other committees. Thus, many of the issues are represented in Working Group activities working towards a specific goal. The challenge still remains to compile all this knowledge and development of tools in a holistic manner in order to provide a working platform for Integrated Coastal Zone Management (ICZM). In order to maintain and improve the quality of ICES advice, the specific requirements for scientific advice in support of client initiatives on ICZM need to be evaluated. These requirements will provide a framework for the ICES advice. Thus, this task should be considered of very high priority. The advice generated from this Study Group will contribute to the goal stated by the Marine Habitat Committee to “Develop procedures for integrated coastal zone management”. The first meeting of the SGINC was opened by the Chair. E. Moksness (Norway) acted as Rapporteur, and the Agenda was adopted (Annex 2). Beatriz Morales-Nin, Director Department Natural Resources, IMEDEA, Spain, welcomed the group.
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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 | 0.022 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 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".