Little Gulls (Hydrocoloeus minutus) in the Hudson Bay Lowlands, Northern Ontario, Canada 1973–2021
Bibliographic record
Abstract
Limited information exists on Little Gulls (Hydrocoloeus minutus) in the Hudson Bay Lowlands, their presumed primary North American breeding site. A 48-year checklist dataset from 1973–2021 in the Ontario portion of the Lowlands combined with a 10-year intensive observation dataset from July to September 2009–2019 in southwestern James Bay, Ontario, reveal key insights. Checklist records consisted primarily of migrants and included 473 Little Gulls (annual mean = 14.8, range = 0–91), with peak numbers (122 individuals) in the third week of May. Intensive observations documented 267 Little Gulls (range = 3–54/year). In the intensive study, adults were first recorded in the third week of July, while second-year birds and juveniles appeared in the first week of August, when all age groups peaked in abundance. The last sightings were juveniles and occurred in the first week of September. This paper advances understanding of Little Gull ecology and migration in North America, emphasizing the necessity for future research. Future studies that employ advanced tracking technology will reveal breeding locations, migration routes, roosting sites, and non-breeding locations, which are vital for the conservation of this enigmatic North American gull species.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".