Eastern Great Lakes Section of the St. Lawrence Seaway
Bibliographic record
Abstract
The Eastern Great Lakes Basin consists of the two primary Great Lakes and many secondary lakes that drain directly through tributaries and into the Great Lakes. The Eastern Great Lakes region covers 51,000 square km of land and is home to 15 million people. This region is rich in natural resources, industry and agriculture, and forms the heartland of both Canada and the United States. The development of this region has a history that is closely tied to waterways and seaways. The development of canals promoted growth and prosperity. The St. Lawrence Seaway connects the Great Lakes to the St Lawrence River and the Gulf of Saint Lawrence. The New York State Canal and the St. Lawrence Seaway were linked by the Oswego Canal and provided a shorter route for cargo via barges to New York City. The New York State (NYS) Barge Canal and the St. Lawrence Seaway provided pathways for the settlement of the Eastern Great Lakes. Lake Erie drains into Lake Ontario via the Niagara River, but the river was not navigable due to the obstacles of Niagara Falls and the Niagara Escarpment. Until the 1820s, ships could not travel into Lake Erie. The Eastern Great Lake shorelines, riverbanks and canals are actively eroding because of high surface water levels and flooding. The primary objective of this paper is to document the environmental risks to the Eastern Great Lakes, the Niagara River and the Welland Canal and to provide a solution to the current deteriorating Welland Canal that needs to be replaced in the next 10 years. The environmental challenges of this region, which require mitigation, include the replacement of the current deteriorating Welland Canal, navigation of the Niagara River, disposal of treated and untreated waste, water pollution, shoreline, riverbank and canal erosion accelerated by high water levels, and buildings on the Eastern Great Lakes shoreline and Niagara Riverbanks, invasive species, and flooding.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.101 | 0.033 |
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".