Preliminary insights into fish movements beyond the massive Iron Gate dams on the Danube River using acoustic telemetry
Bibliographic record
Abstract
Upstream fish movement in the Danube River at the Iron Gate is blocked by the massive hydropower dams and ship locks, as shown by tracking six fish species (vimba bream Vimba vimba, common nase Chondrostoma nasus, barbel Barbus barbus, asp Leuciscus aspius, Pontic shad Alosa immaculata and common carp Cyprinus carpio). In the absence of effective fish passage systems, the current level of river connectivity is insufficient to support upstream movement and migration for this diverse, multispecies fish community. The tagged cyprinids displayed evidence of migratory behaviour. Individuals of vimba bream, barbel, asp and common nase that were transported across the lowermost dam and released into the lower reservoir section showed rapid upstream movement, suggesting that the reservoir itself did not present significant obstacles to migration. Some covered the entire 76-km long reservoir within a few days to 2 weeks but were ultimately blocked by the next dam. Cyprinids released below the dams were recorded at varying depths and on both sides of the river. Asp, barbel, common nase and vimba bream moved both upstream and downstream relatively close to the surface below the Iron Gate II dam, averaging 2-3 m below the surface, but also diving down to about 10-20 m. Future studies combining three-dimensional telemetry methods and detailed information on hydrology below the dams could provide further information on the behaviours of the different fish species, which is needed to design efficient fish passage solutions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".