Bibliographic record
Abstract
oosing is a well known means of capturing birds for banding and marking, although noose designs and capture techniques vary widely (see McNicholl 1983).The noosing technique reported here was used to capture adult Great Cormorants (Phalacrocorax carbo) at a breeding colony on Prince Edward Island, during a study of breeding parameters of this species and Double-crested Cormorants (P.auritus) from 1976 to 1979 (Hogan 1979).According to Lewis (1929), Double-crested Cormorants were captured for food by Indians with nooses, and adult Pelagic Cormorants (P.pelagicus) have been captured with padded leghold traps (Tenaza 1966).Great Cormorants in North America breed in colonies on seacliff ledges, on the level ground at the tops of cliffs, or on small, coastal islands.They rarely nest in trees (Godfrey 1966, pers.obs.), a habit common to other races of this widespread species elsewhere (Cramp and Simmons 1977).While they often nest apart from other species, they occasionally share nesting colonies with Double-crests.Between 1976 and 1979 there were 6 Great Cormorant colonies on Prince Edward Island containing a maximum 738 nests (Hogan 1979).By 1983 there were 8 colonies containing 1324 nests (Hogan 1983).All colonies are on sandstone seacliffs ranging in height from 6 to 33 m.Between 1974 and 1978 I banded 538 Great Cormorant nestlings at the breeding colony on Durell Point, on the east coast of the island.The majority of nests (approx.95%) were built on the upper sloping shelves of the 12-27 m high cliff and were readily accessible.In addition, 51 adults were captured with a noosing pole modified from a similar technique used by Edgar (1968) for Australian Gannets (Sula serrator).A diagram and details of the device are shown in Figure 1.The noosing pole was constructed by a local tinsmith.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".