Staging Little Gulls, Larus minutus, on the Niagara River, Ontario: 1987-1996
Bibliographic record
Abstract
Since its first definite sighting in Ontario in 1930, the Little Gull (Larus minutus) has become an uncommon, but increasingly regular, migrant in the Great Lakes region on its way to and from the wintering areas on the Atlantic seaboard and Mississipi River.Over a period of 10 years (1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996), Little Gulls and Bonaparte's Gulls (Larus philadelphia) were counted as they flew over the Niagara River, Niagara-on-the-Lake, to their nocturnal roost in Lake Ontario to document the timing of migration and to monitor gull numbers.Counts generally began in October or November (range 3 October -21 November) and continued until the fly-past ceased for winter; counting was resumed in early spring to document spring migration return dates.Altogether, 768 Little Gulls were counted and the vast majority (64.9%) of these were in the 1994/1995 (214) and 1995/1996 (285) seasons.This was not due to variation in coverage; in 1994/1995 no counts were made in the autumn season and were made only from 13 January to | May (n = 11).In the seasons for which coverage was similar there was a marginally significant increase in numbers of Little Gulls counted during the spring season, whereas there was a decrease in autumn counts.A comparison of Little Gull counts made at the Niagara River with those made at other staging areas in Ontario indicated that the Niagara River and Long Point may be the most important staging areas on the continent.Recent declines at Long Point coincide with an increase on the Niagara River, suggesting that preferred feeding areas have changed.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".