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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".