Effects of low-head barriers on stream fishes: taxonomic affiliations and morphological correlates of sensitive species
Bibliographic record
Abstract
Low-head barriers used in the control of parasitic sea lamprey (Petromyzon marinus) in the basin of the Laurentian Great Lakes can alter the richness and composition of nontarget fishes in tributary streams. Identification of taxa sensitive to these barriers is an important step toward mitigating these effects. Upstreamdownstream distributions of fishes in 24 pairs of barrier and reference streams from throughout the basin were estimated using electrofishing surveys. For 48 common species from 34 genera and 12 taxonomic families, 819 species, 516 genera, and 27 families showed evidence of being sensitive to barriers, with the variation in number depending on the statistical measure applied. Barriers did not differentially affect species from certain genera or families, nor did they affect species of certain body form. Therefore, taxonomic affiliation and swimming morphology are not useful for predicting sensitivity to barriers for fishes that co-occurred with sea lampreys but were not sampled adequately by our survey. Our estimates of sensitivity will help fisheries managers make sound, defensible decisions regarding the construction, modification (for fish passage), and removal of small, in-stream barriers.
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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 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".