Implementation of community based ocean observatories on the West Coast of Canada
Bibliographic record
Abstract
Ocean Networks Canada submitted a proposal to Western Economic Diversification Canada (WED) in 2014 to develop ocean monitoring infrastructure using advanced sensing technologies in areas critical to BC's economic future, such as the proposed LNG facilities at Campbell River, and the ports of Kitimat and Prince Rupert. The proposed infrastructure included technology related to monitoring maritime risks such as earthquakes and tsunamis; events that would likely be devastating to shipping and port facilities. The sensing technologies selected for these stations were based on meeting a diverse set of requirements, from wave and current conditions at key locations, to the ship traffic navigating those waterways, to monitoring baseline oceanographic conditions and to providing ocean data of interest to the communities supporting the observatories. The core observatory infrastructure includes a shore station with power and communications, cable solutions for terrestrial and subsea environments, and the sensor systems themselves. In the final months of 2015 and the first quarter of 2016, a series of Community Observatories up the Coast of British Columbia were developed. This paper will provide an overview of the technologies at each site and the justification for why these sites are important to monitor. The challenges related to developing the infrastructure will be addressed, and strategies employed to improve installation reliability and robustness will also be discussed. Details related to the ONC shore station will be covered, including ongoing challenges associated with reliable communications in small communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".