Habitat Use by Least Bitterns (<i>Ixobrychus exilis</i>) in Québec
Bibliographic record
Abstract
Wetland-scale and landscape-scale descriptors were compiled at 123 wetlands where Least Bittern (Ixobrychus exilis) have been detected in Québec since 1986 to identify key attributes associated with Least Bittern occurrence. Land cover information extracted from Landsat-7 ETM imagery and road density were calculated for a 500-m buffer surrounding occupied wetlands and paired sites ten km away to compare to the regional landscape. Cattail (Typha spp.) was the dominant vegetation at 96 of 123 wetlands. Shrub swamps were used at eleven sites. Wetland area ranged from 0.5 ha to 983 ha and man-made impoundments accounted for 24% of occupied sites. The 500-m buffer surrounding occupied wetlands was dominated by urban areas, agriculture, forests or wetlands at four, 22, 21 and 32 sites, respectively. Mean wetland cover was higher in the 500-m buffer (37%) than in the regional landscape (4%) whereas agriculture cover was greater at paired sites (55%) than around occupied wetlands (28%). Cover of anthropogenic and forest areas did not differ between wetland buffers and paired sites. Mean road density was higher in the 500-m buffer around occupied wetlands (29.5 m/ha) than in the regional landscape (18.4 m/ha) suggesting that wetlands near roads may be more easily accessible to surveyors. Habitat use in Québec corresponds with known breeding habitat structure elsewhere in North America. Along with wetland creation and conservation initiatives of remaining small and large wetlands, Least Bittern conservation will benefit from regular monitoring of impoundments' operable conditions to prevent sudden habitat changes that may impact breeding birds.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".