Gravel washing as a lacustrine spawning habitat restoration method for smallmouth bass
Bibliographic record
Abstract
Smallmouth bass ( Micropterus dolomieu ) spawn on gravel and cobble in the littoral zone of lakes that may become degraded by the presence of fine sediments and decomposing organic matter. Substrate size and composition have been identified as important variables for nest site selection by male smallmouth bass. We tested whether ‘cleaning’ substrate by removing sediment with a pressure washer would increase the number of bass nests or the average total length (mm) of nesting smallmouth bass in selected areas of Big Rideau Lake, Ontario, Canada the following year using a before-after control-impact design. Treatment was not a significant predictor of nest abundance or average male length. Considering the strength of the experimental design it is reasonable to conclude that this intervention failed to enhance spawning substrate for smallmouth bass. Understanding the factors that maintain productive spawning sites for smallmouth bass is important to restoration effectiveness and determining where habitat enhancement will provide the greatest benefits.
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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 | 0.001 |
| 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".