Report of the Study Group on Ecosystem Assessment and Monitoring (SGEAM)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The presentations of national and international activities related to the work of SGEAM demonstrated that ecosystem-based management and the development of indicators have become adopted by certain Member Countries, notably; the UK, Norway, Canada and the Baltic States. The methods being developed by these countries will help influence the development and implementation of an ICES-wide ecosystem-based assessment and management approach. SGEAM therefore recommends that ICES establish Regional Ecosystem Groups, REGs, to undertake the compilation and assessment of the periodic status reports from the various ICES working groups. <br> SGEAM recommends that ICES as a beginning establish an REG for the North Sea to meet the invitation from the Bergen Declaration, which was the conclusion of the Fifth North Sea Conference held in Bergen on 20 and 21 March 2002. SGEAM also recommends, as it did in 2001, that a REG for the Baltic Sea be established. SGEAM also proposes a framework for the preparation of environmental data and assessment reports on a regular basis. <br> SGEAM also recommends its termination, but recommends that a permanent working group should be established. Although the participation at the SGEAM meetings has not been particularly representative for the combined activities of ICES, SGEAM is of the opinion that there is a need for a forum within ICES where questions on how the ecosystem-based management approach can be implemented can be raised and discussed. A permanent working group will also be a valuable forum for exchange of national views on the development of indicators and for harmonizing the various approaches to ecosystem management.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it