DENSITY INFLUENCES CENSUS TECHNIQUE ACCURACY FOR CERULEAN WARBLERS IN EASTERN ONTARIO
Bibliographic record
Abstract
This study investigated the accuracy of 50-m fixed-radius, 100-m fixed-radius, and variable circular-plot point counts to estimate the actual density of breeding Cerulean Warblers (Dendroica cerulea) during the 1997 and 1998 breeding seasons, in Ontario, Canada. Density estimates were compared to actual densities as measured from intensive field observation of pairing and nesting behavior. Estimates of density from each of the techniques were positively correlated with actual density in both years. Both the technique used to census a population as well as the actual density of the population itself affected the accuracy of the derived density estimations. In both years, the 50-m fixed-radius technique overestimated density. In contrast, the 100-m fixed-radius technique and variable circular-plot technique underestimated density; the degree of the underestimate of the 100-m fixed-radius increased as actual density increased. There was no correlation between the degree of underestimation and actual density for the variable circular-plot technique. Although all three methodologies provide relative measures of density, the variable circular-plot technique provides the best absolute assessment of Cerulean Warbler density and is considered most suitable for broad-scale surveys.
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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 | 0.001 | 0.014 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".