Who is the better candidate? Macroinvertebrates and diatoms for ecological status assessment of Sava Lake (Serbia)
Bibliographic record
Abstract
Sava Lake was created from the right arm of the Sava River, and the inhabitants of Belgrade use the lake intensively for swimming and bathing. We analysed macrozoobenthos and epilithic diatom communities at six sites from April to October 2017, to assess the ecological status of Sava Lake according to the National legislation of Serbia. Considering macrozoobenthos communities, the mean values of Zelinka and Marvan saprobity index indicated high ecological status. In contrast, results obtained from the mean values of BMWP (Biological Monitoring Working Party) scores suggested moderate to poor ecological status. The mean values of the IPS diatom index (Indice de Polluo-sensibilité) indicated high ecological status, while the TDIL index (Trophic Diatom Index for lakes) was slightly more sensitive and indicated good ecological status. Water chemical parameters indicated that Sava Lake was mainly oligotrophic during the study period (average total phosphorus concentrations were 10.7 μgL-1 and average total nitrogen concentrations 410 μgL-1). Before being able to adopt an integrative approach for ecological status assessment (combining two or more biological quality elements), more studies must be performed on how to choose the most sensitive and adequate indices. This is especially true for lakes experiencing intensive anthropogenic pressure during the summer season. Also, the boundary values in the National legislation of Serbia must be adapted for lakes, such as Sava Lake.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".