Estimating Trumpeter Swan (Cygnus buccinator) Populations in Alberta and Response to Disturbance
Bibliographic record
Abstract
Trumpeter Swans (Cygnus buccinator) were once widespread across much of North America, but after years of exploitation were reduced to near extinction. This research addressed the extent that human disturbance is affecting Trumpeter Swan breeding productivity and developed a more efficient survey method for populations in Alberta. Disturbance experiments were conducted using a pedestrian to determine the range a disturbance response is elicited. The relationship between swan breeding productivity and distances to landscape human features around nesting lakes was examined using linear regressions. Trumpeter Swans had a maximum escape distance of 1179 m and an average escape distance of 736±46 m (n=19). Disturbance models involving well sites (p=0.033), power lines (p=0.004), and cut lines (p=0.032) in 2010 were significant. Stratified Random Sampling accurately estimated Trumpeter Swan populations in 2000 and 2005 using strata of 0, 1-50, 51-100, and 101+ swans per survey block.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".