Fish use of stage-specific fluvial habitats as refuge patches during a flood in a low-gradient Illinois stream
Bibliographic record
Abstract
A stage-specific habitat classification scheme was developed emphasizing the ecological importance of habitat space as flow refugia for fish. Habitat units were based on planform and channel morphology and the resulting three-dimensional hydraulic patterns that form during floods. Fish were sampled in specific habitat patches using prepositioned areal electrofishing devices at two high-flow stages, near bankfull flow and one-half bankfull flow, during a flood. Fish were also sampled at baseflow immediately following the flood to compare changes in habitat use related to flow stage. During the bankfull stage, fish were found to use floodplain habitat units identified as vegetated point bars and concave-bank benches. During the one-half bank-full stage, fish density and biomass were greater in low-velocity habitat units identified as deflection eddies and expansion eddies than in the high-velocity habitat unit identified as the channel thalweg. Once flow returned to baseflow, fish density and biomass were greater in the main channel habitat units (pools, riffles, and glides) than in lateral habitat units identified as submerged point bars and lateral backwaters. This study provided a framework to quantify flow refugia in low-gradient streams, which is especially important in the restoration of anthropogenically disturbed watersheds that have lost habitat connectivity.
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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 | 0.001 |
| 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".