Habitat occupancy by Spruce Grouse (<i>Canachites canadensis</i>) in the south of its range in Quebec, Canada
Bibliographic record
Abstract
Studying habitat occupancy at the margins of the distributions of species can be helpful in clarifying the requirements of species and planning management measures. Spruce Grouse (Canachites canadensis (Linnaeus, 1758)), a bird species associated with northern short-needle coniferous forests in North America, has its southeastern range limit where coniferous forests are mixed with temperate deciduous forests and agricultural lands. Some isolated populations are found in these habitats. Using a single-season occupancy modelling approach, we investigated habitat use by Spruce Grouse, accounting for imperfect detection, in the lowlands of the St. Lawrence River in southern Quebec, Canada. We conducted call-response surveys of Spruce Grouse over three years at 279 sites (59 sites in 2007, 100 sites in 2008, and 120 sites in 2009). At the site level, the probability of occupancy was 21% (95% confidence interval (CI) = 10.7%–37.9%) and probability of detection was 54% (95% CI = 34.7%–73.0%). Based on the covariates in the models, occurrence increased with higher cover of coniferous trees and low deciduous shrubs, and decreased with higher cover of deciduous trees. Finally, detection probability was highest at the beginning of the survey (50% in late April) and was influenced by year.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".