Bibliographic record
Abstract
With harsh Arctic conditions prohibiting easy, year-round access to subsea assets due to surface ice and weather conditions comes the need to create subsea monitoring technologies capable of reliably surviving long term deployments with little or no intervention. High capacity battery pods and UPSs provide an ideal power delivery method for subsea systems when surface ice and inclement weather precludes the use of buoys or other surface based options. To provide continuous monitoring of subsea conditions throughout the seasons where access is limited, a high capacity battery pod or UPS can be used as the base of a moored array. The battery pod or UPS would act as the primary source when the site is inaccessible, allowing the continued polling and control of a variety of systems and sensors throughout the year. Logged data can then be relayed to a shore station or other common data management point. This paper focuses on high capacity battery pod and UPS applications specific to an Arctic environment where long term monitoring can be enhanced with the use of an in-situ energy reservoir. In addition, example systems and applications are presented.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".