A comparative study of four indexes based on zooplankton as trophic state indicators in reservoirs 2019. Volumen 38 (1): 291-302
Bibliographic record
Abstract
This study aims to examine four recently conducted trophic state indices that are based on the density of zooplankton and designed for estimating the trophic state of inland waters. These indices include two with formulations based on quotients or ratios, the Rcla and the Rzoo-chla, which were proposed and validated in the European project ECOFRAME, and two with formulations based on the incorporation of a statistical tool comprising canonical correspondences analysis (CCA), the Wetland Zooplankton Index proposed in 2002 by researchers from McMaster University of Ontario and the Zooplankton Reservoir Trophic Index, an index recently designed by the Ebro Basin Authority and on which this manuscript is the first article. These indices were studied and applied in 53 heterogeneous reservoirs of the Ebro Basin. In addition, all were subsequently validated by Carlson's Trophic State Index based on the amount of chlorophyll-a, with significant differences found between them.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".