Breeding density and breeding phenology of Nelson's Sparrows (Ammodramus nelson) in saltmarsh and inland habitats
Bibliographic record
Abstract
The Nelson's Sparrow (Ammodramus nelsoni) is a small, secretive songbird that breeds in marsh habitats along the coast of Atlantic North America, and is strongly associated with saltmarshes in the Maritime Provinces. In 2012, I studied the breeding density and breeding season duration of Nelson's Sparrows in both saltmarsh and inland wetland habitats at the Beaubassin Research Station near Aulac, New Brunswick. A total of 20 point count stations were selected, 10 stations within the boundaries of the saltmarsh habitat and 10 stations within inland habitats among freshwater marshes. Point counts were conducted beginning in mid-June, when it became apparent that the sparrows had returned to the property, through to late July (15 days over this period). During the initial 10 sampling days in June, there were consistently higher numbers of male sparrows singing (an indication of breeding) in the saltmarsh habitat than in inland habitats. However, no significant difference in breeding activity existed for the habitats during the weekly July counts. Although Nelson's Sparrows at the Beaubassin Research Station will breed primarily in the saltmarsh, results suggested that they will also breed in suboptimal habitats located inland. Nonetheless, its apparent preference for the saltmarsh may allow the species to serve as a suitable bioindicator of saltmarsh quality across parts of Canadian Maritime coasts.
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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 | 0.000 | 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".