Bibliographic record
Abstract
The following data show the distribution of Canada Geese (Branta c. canadensis), banded in the James Bay area of Canada: Charlton Island, N.W.T. (100); Akimiski Island (1,000); and near Seneca Falls, New York (253).Charlton Island is approximately 75 miles east of Moosonee, Ontario, Canada, and Akimiski Island is approximately 135 miles north of Moosonee.Seneca Falls in located in the Finger Lakes area of north central New York.This is no attempt to arrive at any particular conclusion.The data are presented for the interest of those banders who do not have the opportunity to handle and band waterfowl.One interesting question arises, which I am not attempting to answer.Both Charlton Island and Akimiski Island are in James Bay and, geographically, only a short distance apart.However, all the recoveries of the Charlton Island birds were in the Atlantic Flyway, while recoveries from the Akimiski Island birds were divided -approximately 75% being in the Mississippi Flyway and 25% in the Atlantic Flyway.Organizations directly contributing to this work are: U.S. Fish & Wildlife Service, Canadian Wildlife Service, and the Ontario Department of Lands and Forests.Individuals contributing are: Alex Hunter (at that time an employee of the Ontario Department of Lands and Forests, who accompanied me on several banding trips into the James Bay country) and Vernon E.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.708 | 0.590 |
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".