Herps in the wind: the ecology of herpetofauna in windfarms
Bibliographic record
Abstract
Windfarms are reducing reliance on fossil fuels but they may present threats to wildlife. I studied \nthe ecology of herpetofauna living in Prince Windfarm (Sault Ste Marie, Ontario) in 4 wetlands \nlocated close to wind turbines (<500 m, Turbine sites), and 4 wetlands far from wind turbines \n(>1.5 km, Control sites). I measured amphibian biodiversity using transect surveys and acoustic \nrecordings of frog calls. I found lower biodiversity and richness within frog choruses in Turbine \nsites, and some evidence that frogs in windfarms adjust their calls similar to frogs near roads. I \nalso investigated whether the spatial ecology of Painted Turtles (Chrysemys picta) was impacted \nby the windfarm. Turtles within the windfarm had shorter movements and marginally smaller \nhome ranges than turtles in Control sites, and appeared to avoid service roads and turbines. \nFuture research should investigate acoustic masking of low frequency calling amphibians and \ninfrastructure avoidance behaviours by turtles.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".