C-SCOUT maneuverability-a study in sensitivity
Bibliographic record
Abstract
In September of 1998, the Institute for Marine Dynamics (IMD) of the National Research Council of Canada and the Ocean Engineering Research Centre of Memorial University of Newfoundland commenced a collaborative effort to design a streamlined autonomous underwater vehicle (AUV). This AUV, the Canadian Self-Contained Off-the-shelf Underwater Testbed (C-SCOUT), is intended to serve as a test bed for systems research; in particular it is expected to assist in the development of control systems and propulsion systems. It is also to be utilized in the testing of vehicle components and as a general research and development tool for years to come. The vehicle is of modular construction, such that its length, and the position of the appendages are somewhat variable. One of the key elements in the vehicle's effectiveness as a test bed is a fundamental understanding of its maneuverability and of its sensitivity to changes in hydrodynamic parameters. Hydrodynamic parameters, however, are typically determined from in-water testing and there is usually some uncertainty concerning their exact values. Knowledge of these vehicle characteristics will allow the systems designer to separate inherent vehicle behaviour from behaviour induced by the system being tested, resulting in a clear measurement of system 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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".