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Building the World's First Multi-node Cabled Ocean Observatories (NEPTUNE Canada and VENUS, Canada): Science, Realities, Challenges and Opportunities

2008· article· en· W2068228757 on OpenAlexafffundabout
Chris Barnes, Verena Tunnicliffe

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Computational Techniques and Applications
Canadian institutionsUniversity of Victoria
FundersDivision of Ocean SciencesNatural Sciences and Engineering Research Council of CanadaCanarie
KeywordsVenusNeptuneObservatoryData archiveOceanographyRemote sensingAstrobiologyMeteorologyTelecommunicationsPlanetComputer scienceGeographyGeologyAstronomy

Abstract

fetched live from OpenAlex

NEPTUNE Canada (North-East Pacific undersea networked experiments) and VENUS (Victoria experimental network under the sea) will be the world's first multi-node cabled ocean observatories, with installation in 2006-08. The abundant power, high bandwidth communications, and hundreds of sensors delivering data and imagery in real or near real time will transform both our acquisition of knowledge and our understanding of the ocean environment. With the world's oceans in a state of crisis, the development of cabled observatory technology is most timely and will offer a data archive of unparalleled importance for new discoveries.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.996
Threshold uncertainty score0.893

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.079
GPT teacher head0.263
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations38
Published2008
Admission routes3
Has abstractyes

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