Cross‐border freight movements in the Great Lakes and St. Lawrence Region, with insights from passive GPS data
Bibliographic record
Abstract
Abstract The Great Lakes and St. Lawrence binational region is one of the most significant concentrations of industrial production on earth and contains the most active corridors for goods movements in the Canada‐United States trade relationship. The history of industrial development in this region involves the exploitation of coal and iron ore for steel production, the development of the railroads and the expansion of commercial agriculture, and the growth of the automotive and other high value‐added manufacturing industries. Canadian and American industrial complexes became increasingly integrated with the support of trade agreements in the latter decades of the 20th century. Development of cross‐border supply chains led to massive international flows of intermediate goods. In this context, the performance of a few key border crossings is of critical economic importance. New information drawn from very large datasets of Global Positioning System records generated by cross‐border truck movements sheds new light on both the spatial patterns of cross‐border goods movement and the performance of border crossings.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".