Cross-biome scale data of summer bird assemblages across various habitat types in Alberta, western Canada
Bibliographic record
Abstract
Alberta covers diverse types of ecosystems including boreal forests, Rocky Mountain subalpine forests, as well as temperate grasslands in western Canada. The location of Alberta at the convergence of the Pacific and Central Flyways highlights its importance for bird conservation. However, recent climate change is altering vegetation, reducing wetlands, which can influence habitat niche availability of birds. While there are certain efforts of bird monitoring, public data are often limited to checklists or species presence, community-level datasets of birds collected consistently across biomes is rarely available. Here I conducted large-scale summer surveys of breeding birds across Alberta’s six major ecoregions (Northern Rockies conifer forests, Alberta-British Columbia foothills forests, Mid-Canada Boreal Plains forests, Canadian Aspen forests and parklands, Montana Valley and Foothill grasslands, and Northern Shortgrass prairie). These surveys span woodlands, wetlands, grasslands, farmlands, and urban areas, providing a comprehensive bird species inventory. This preliminary dataset establishes a baseline for understanding avian biodiversity across Alberta and supports future research and conservation strategies aimed at mitigating climate-induced habitat changes.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".