Development of the EcoQO for the North Sea fish community
Bibliographic record
Abstract
Abstract Greenstreet, S. P. R., Rogers, S. I., Rice, J. C., Piet, G. J., Guirey, E. J., Fraser, H. M., and Fryer, R. J. 2011. Development of the EcoQO for the North Sea fish community. – ICES Journal of Marine Science, 68: 1–11. Development of the Ecological Quality Objective (EcoQO) for the North Sea demersal fish community is described. Size-based metrics were identified as the most effective indicators of the state of the community, but such metrics are also sensitive to environmental influence. Redefining the large fish indicator (LFI) produced a metric more sensitive to fishing-induced change and therefore more useful to managers. Fish stocks were thought to be exploited at a sustainable rate in the early 1980s, so in a process echoing the precautionary approach to fish stock management, this was considered the reference period for the LFI, suggesting a value of 0.3 as the appropriate EcoQO. The LFI declined from around 0.3 in 1983 to 0.05 in 2001, followed by a recovery to 0.22 in 2008. However, analyses of the longer-term groundfish survey data suggest that, even were fishing pressure to be reduced to early 20th century levels, the LFI would be unlikely to rise much above a value of 0.3. The response of the LFI to variation in fishing pressure suggested a more complex relationship than anticipated, underscoring the need for operational theoretical size-resolved multispecies fish community models to support management towards broader ecosystem objectives.
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 | 0.022 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".