Data from: Freshwater Habitats in Natura 2000: Gaps in Prioritization and Protection
Bibliographic record
Abstract
Freshwater biodiversity is experiencing dramatic declines both globally and in Europe. Despite improvements over the last decades, the overall trend remains negative, underlining that effective and coordinated initiatives are needed. In this study, we explore the representation of freshwater habitats in the Natura 2000 network to assess whether conservation and restoration measures within the network can contribute significantly to reverse freshwater biodiversity declines. Specifically, we provide an overview of freshwater habitats listed in the HD Annex I within the Natura 2000 network, evaluating their representation, coverage, and distribution including all surface- and groundwater-dependent ecosystems. Data were extracted from the Natura 2000 database (version 2021; EC, 2022). We used datasets “NATURA2000SITES” (in all three datasets), “HABITATS” (in datasets 2_habitats_all and 3_habitats_freshwater), and “BIOREGION” (in dataset 3_habitats_freshwater).
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.008 |
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".