Best practices for operating underwater gliders in Atlantic Canada
Bibliographic record
Abstract
Ocean gliders are versatile tools for making ocean observations. This paper summarizes the experience, of nearly two decades, of glider observing activity in Atlantic Canada. It reviews key considerations for operating gliders based on the experience and the lessons learned. This paper has three main goals: 1. To provide new and emerging glider users with guidance and considerations for developing a glider program. 2. Review the literature on sensor development for gliders and the use of gliders. 3. To highlight different mission scenarios that include enough practical considerations to support operating gliders. The use of gliders is rapidly expanding, but the documentation and consolidation of best practices for their operational use in Atlantic Canada remains underdeveloped. This summary provides a guide that should be helpful both to new and experienced glider operators and potential users, to observe the oceanography of this region and addresses regional challenges. We believe documenting our experience will be also helpful to the global glider community. We summarize the most critical considerations of utilizing gliders. We review the issues specific to the platform use and concerns about how to optimize the use of key sensors to contribute to an oceanographic observing program.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".