Management of the Great Lakes-St. Lawrence Maritime Transportation System
Bibliographic record
Abstract
The Great Lakes-St. Lawrence Maritime Transportation System ("MTS") bears critical importance to the economic competitiveness of Canada and the United States ("US"). Maritime transportation comprises both a major economic driver and job creator for both countries. As a cost-effective and highly efficient means of transporting raw materials and finished products to market, the MTS is essential to agricultural, mining, and manufacturing supply chains that frequently stretch across the US-Canada border and beyond. Yet management of the MTS is fragmented, with responsibility for various system components scattered across numerous federal agencies in both the US and Canada. This fragmentation results in a dearth of transparency, confusing and disjointed governmental authority, higher user costs, barriers to establishing new markets, and overall reduced system competitiveness. The development of a treaty that commits both nations to integrate system management, harmonize regulations, and promote more effective coordination will bring clarity regarding authority over key system aspects, increase accountability, and improve performance.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".