Evaluation of the Ecological Environment of the Fuhe River Based on the Diversity of Fish
Bibliographic record
Abstract
This article takes the Fuhe River, which has water flowing into Baiyangdian all year round, as the research object. Through actual investigation and measurement of planktonic flora and fauna, benthic organisms, fish, and large vascular plants in the river, and based on fish diversity, the comprehensive evaluation index method is used to scientifically evaluate the ecological environment quality of the Fuhe River. The results showed that a total of 28 species of phytoplankton, 30 species of zooplankton, 11 species of benthic animals, 8 species of submerged plants, and 11 species of fish were detected in the survey area; From a diversity perspective, the diversity of the upstream and downstream river sections is higher than that of the downstream. Overall, the ecological environment quality of the Fuhe River in Baoding City ranges from medium to good, with good water quality in the upstream section and moderate water quality in the middle and downstream sections. This study provides a case study for the scientific evaluation of the ecological environment quality of the upper reaches of Baiyangdian.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.001 | 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".