Historical ice thickness and plausible climate change effects on the upper St. Lawrence River
Bibliographic record
Abstract
The St. Lawrence River is an important trade corridor with significant vessel traffic and hundreds of infrastructure assets, such as ports, docks, dams, hydroelectric facilities and locks. The safe and effective operation of existing seaway assets, and the design of new infrastructure, depend on many environmental factors. The expected effects of climate change must be considered when planning future operations and construction. One concern for seaway operations is ice. An ice cover forms seasonally along most of the marine corridor from the Great Lakes to the Gulf of St. Lawrence. To evaluate the historical ice conditions along the upper St. Lawrence River, data are xamined for the section from the Iroquois Dam to Montreal, Quebec. Maximum annual shorefast ice thickness is determined from on-ice measurements, and compared to freezing degree day calculations based on air temperatures from weather stations and climate model hindcasts. Plausible future ice thicknesses are assessed from estimated freezing degree days using climate-modelled future air temperatures as input. Maximum annual ice thickness has declined over the past 70 years, and is expected to continue to decline in a warming climate.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".