Good-Moderate boundary setting for the environmental status assessment of the macrozoobenthos communities with the Benthic Quality Index (BQI) in the south-western Baltic Sea
Bibliographic record
Abstract
The status assessment of the macrofauna community under the European Marine Strategy Framework Directive (MSFD) requires threshold values that mark the transition from good to moderate conditions (G-M boundaries). Using the example of the Benthic Quality Index (BQI) in the south-western Baltic Sea, we demonstrate the possibilities and restrictions of i) defining G-M boundaries using reference areas, historical data and a statistical method and ii) the subsequent evaluation of the resulting G-M boundaries using disturbance data. The historical data from the period 1911 to 1929 proved to be unsuitable for defining G-M boundaries due to their data quality. The G-M boundaries calculated using the statistical method delineated high disturbance values more reliably than those based on reference areas. We conclude that disturbance data are very useful to evaluate G-M boundaries for their suitability, but data on all state conditions are needed.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".