MétaCan
Menu
Back to cohort
Record W7132010060

Web-based geospatial decision support system to facilitate marine renewable energy site selection in British Columbia, Canada

2018· article· en· W7132010060 on OpenAlexafffundvenueabout
Sean Ferguson, Julien Cousineau

Bibliographic record

VenueNPARC · 2018
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsNational Research Council Canada
FundersNatural Resources CanadaBC Hydro
KeywordsGeospatial analysisDecision support systemSite selectionRenewable energyAtlas (anatomy)Spatial decision support systemHotspot (geology)Geographic information system
DOInot available

Abstract

fetched live from OpenAlex

The authors present the British Columbia Marine Energy Resource Atlas (hereafter referred to as “the Atlas”), a web-based geospatial decision support system (DSS) to facilitate preliminary marine renewable energy (MRE) site selection and feasibility investigations within the rivers and coastal waters of Canada’s westernmost province. The Atlas was developed such that users are able to interact with the underlying datasets that drive the hotspot delineation. As such, the Atlas is an effective tool to quickly investigate multiple case-scenarios with different resource, socio-economic, and environmental criteria. Furthermore, the Atlas is the first MRE DSS to offer support for tidal, wave, and river hydrokinetic resources under a common system and interface.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.180
Teacher spread0.173 · 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
GenreEmpirical

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

Citations0
Published2018
Admission routes4
Has abstractyes

Explore more

Same venueNPARCSame topicWind Energy Research and DevelopmentFrench-language works237,207