Using Ship Speed and Mass to Describe Potential Collision Severity with Whales: An Application of the Ship Traffic, Energy and Environment Model (STEEM)
Bibliographic record
Abstract
This paper presents an application of the Ship Traffic, Energy, and Environment Model (STEEM) to estimate and visualize the risk and severity of collision between ships and the North Atlantic Right Whales along the U.S. and Canadian Atlantic coast. According to the physics of the interaction between a ship and a whale, for ships larger than 500 tons, speed is more important than the size of a ship in determining a lethal injury to a whale. Reducing ship speed could reduce the ton-force significantly. The visual representation of the risk and potential severity of ship-whale collision along the U.S. and Canadian Atlantic coast shows that the coast between Jacksonville, FL and Savannah, GA, the major shipping lanes of Cape Cod, the mouth of Bay of Fundy, and the area south to Nova Scotia, Canada (Roseway Basin) are the areas with highest risk of severe or lethal injury due to a ship strikes. On the waterway network the distribution of ton-force of ship traffic is rather uniform, and thus, the distribution of whales rather than ton-force determines the distribution of risk of potential severity of injury to whales.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".