Bibliographic record
Abstract
Abstract Stretching between the two countries for more than 5000 miles, the boundary between the United States and Canada is described as the longest undefended border in the world. More than 200 million people cross the border annually, making it the world’s largest trading relationship. Bilateral trade between the two countries is valued at close to $680 billion Canadian dollars. More than $1.5 billion dollars is exchanged across the border on a daily basis.2 Extensive partnerships between the United States and Canada govern this border. From the Free Trade Agreement (FTA) and North American Free Trade Agreement (NAFTA) to North American Aerospace Defense Command (NORAD) and North Atlantic Treaty Organization (NATO) military accords, the list of bilateral initiatives between the two countries is extensive. The author would like to thank Robert Smith, Celiany Rivera-Velazquez, Amy Hasinoff, Aisha Durham, Himika Bhattacharya, Helen Kang, Carolyn Randolph, Jillian Baez, Kent Ono, C. L. Cole, Paula Treichler, Ian Kerr, Jane Bailey, Daphne Gilbert, and the anonymous reviewers for their helpful suggestions.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".