Review of Ice-Control Methods at Lock 8, Welland Canal, Port Colborne, Ontario
Bibliographic record
Abstract
Abstract : This effort reviews the existing procedures and equipment used at Lock 8 on the Welland Ship Canal, Ontario, Canada, to control ice and to reduce the possibility of ice causing a shipping vessel to get stuck or jammed in the lock chamber. The lock uses several methods, including an air curtain to hold ice above the lock, bubblers and mechanical means to reduce the ice accumulation on the lock walls, and bubblers to flush ice from the gate recesses. A review of all of these methods shows that mostly they have been effective, though some recommended modifications include reducing the air-curtain and bubblers nozzle size to make the flow across the manifolds more uniform. The only system that the St. Lawrence Seaway Management Corporation might consider replacing entirely is the blaster bubblers, which are unreliable and ineffective. This report details recommended improvements to ice control at Lock 8, including a secondary air curtain below the existing air curtain, a manifold recess bubbler, and methods to further reduce the quantity of ice passing through the breakwater and bypassing ice down the weir channel. Further work is required to determine feasibility and the final design for each of these recommended changes.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".