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Record W2031204390 · doi:10.1109/oceans.2008.5151869

SmartBay: Better Information - Better Decisions

2008· article· en· W2031204390 on OpenAlexaffabout
Bill Carter, Stephen Green, Robert Leeman, Neil Chaulk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The SmartBay initiative (www.SmartBay.ca) is led by the School of Ocean Technology, part of the Fisheries and Marine Institute of Memorial University of Newfoundland located in St. John's, Newfoundland. The SmartBay team includes industry partners AMEC Earth and Environmental, International Communications and Navigation (ICAN) Limited and Earth Information Technologies (Nfld) Limited. The vision of SmartBay is "to provide simple access by all stakeholders to data and information in support of effective management and sustainable development of coastal ocean areas and the safety and security of life at sea". Accordingly, SmartBay has been implemented as a user-driven ocean observing system, serving the information needs of the users of Placentia Bay, Newfoundland (including fishermen, the oil industry, marine transportation, recreation, municipalities and the people who live there) in support of better decision-making. The applications of SmartBay have been just as varied, ranging from safety and marine efficiency, to industrial development, to community socio-economics and environmental protection. Hence the motto: "Better Information - Better Decisions". Placentia Bay is rapidly becoming the industrial heartland of Newfoundland and Labrador and with this come the challenges and complexities of mixing traditional and non-traditional users and uses, as well as a host of safety, environmental and regulatory concerns. The basic premise of SmartBay is to integrate and deliver information created from both static and dynamic data in a manner best suited to the particular needs of a broad base of users. The incidental or non-professional user can access the information through a web portal requiring no special hardware or services. The mariner is able to access and display information on an electronic chart using standard bridge hardware and communications systems. SmartBay also supports the interests of a third class of user, "the professional", engaged in roles ranging from fisheries management to oceanographic research to environmental protection to sovereignty and security. After approximately 18 months of operation SmartBay has become a prominent feature of the Placentia Bay seascape. There are currently three SmartBay buoys positioned in the Bay. A 3-metre met/ocean buoy near the mouth of the bay provides critical data to support weather and sea state forecasts; a customized water quality buoy off Come by Chance Point provides met/ocean as well as water quality information for this high traffic area; and a water quality buoy fitted with meteorological sensors off Rushoon on the western side of the bay supports an emerging aquaculture industry in the area. In addition, St. John's based Institute of Ocean Technology (IOT) has provided a wave buoy for term deployments at the pilot boarding station located just south of Red Island Shoal. Included within the dynamic information provided to the Placentia Bay user community is custom weather and sea state forecasting (utilizing buoy program data), and vessel reporting and monitoring (utilizing Automatic Identification System (AIS) technology). In addition, SmartBay is the information dissemination medium for ongoing time-series water quality data acquired by the provincial Department of Fisheries and Aquaculture. As a demonstration project, SmartBay has been successful, so much so that the community, both in and beyond Placentia Bay, has come to rely on it to the extent that SmartBay is regarded by many as an essential service. In response, SmartBay has been maintained as a 24/7/365 operation, along the way facing significant financial and technical challenges. Interest in the SmartBay concept from other parts of the province reflects grass roots demand for better information. This local interest represents the catalyst for a series of local coastal ocean observing system initiatives. Using SmartBay as a template, each system can be developed to meet local needs and priorities. By designing local systems around a common high-level architecture they will ultimately coalesce to form a sustainable, province-wide infrastructure to support sustainable development of coastal ocean spaces, resources and 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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.667
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.014
GPT teacher head0.218
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations15
Published2008
Admission routes2
Has abstractyes

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