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Record W2152270434 · doi:10.1109/oceanse.2005.1513188

An acoustically-linked deep-ocean observatory

2005· article· en· W2152270434 on OpenAlexaboutno aff
Daniel E. Frye, Jonathan Ware, M. Grund, Jim Partan, Peter Koski, Sandipa Singh, Lee Freitag, J. A. Collins, R. S. Detrick

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsnot available
FundersWoods Hole Oceanographic InstitutionNational Science Foundation
KeywordsBuoySeismometerObservatoryGeologyComputer scienceRemote sensingSubmarine pipelineSeismologyOceanography

Abstract

fetched live from OpenAlex

A buoy-based observatory that uses acoustic communication to retrieve data from water column and seafloor instruments has been developed and deployed in 2362 m of water offshore Vancouver Island. The system uses high-rate (5000 bps) acoustic modems that are power-efficient (on order 1000 bits per joule) to telemeter data from an ocean bottom seismometer and a sensor monitoring a cold seep site near the Nootka fault. The buoy includes a Linux-based embedded controller, the modem base station and meteorological sensors. Data is off-loaded from the buoy using ftp, and remote login capability allows the acoustic communication schedule to be modified when instruments are added or removed from the network. The system has been operational for one year, typically transferring more than 500 Kbytes of data per day from two seafloor instruments.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.019
GPT teacher head0.229
Teacher spread0.210 · 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 designBench or experimental
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

Citations23
Published2005
Admission routes1
Has abstractyes

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