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Record W1963827993 · doi:10.1121/1.4830477

Measurement of hydrothermal heat flux using a sonar deployed on the Canadian Neptune cabled observatory

2013· article· en· W1963827993 on OpenAlexaboutno aff
Guangyu Xu, Peter A. Rona, K. G. Bemis, Darrell R. Jackson

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsNeptunePlumeObservatoryGeologySonarHeat fluxFlux (metallurgy)Doppler effectGeophysicsRemote sensingGeodesyEnvironmental scienceMeteorologyPhysicsOceanographyMaterials scienceAstronomyHeat transferMechanicsPlanet

Abstract

fetched live from OpenAlex

The Cabled Observatory Vent Imaging Sonar (COVIS) was deployed at the Main Endeavour Field node of the Canadian NEPTUNE cabled observatory in September 2010 and has acquired long time series on plume and diffuse hydrothermal flows. This talk will focus on recent efforts by the Rutgers-APL collaboration to invert sonar data to determine heat flux from the Grotto plume complex. Inversion employs plume theory to relate velocity as determined by Doppler shift to buoyancy flux, hence heat flux. The primary uncertainties have to do with plume bending due to ambient current and short sampling times relative to dynamic changes in plume shape. These uncertainties have been quantified by means of special high-statistics experiments using COVIS. Time series for heat flux will be compared with ground truth obtained by thermometry using an ROV. [Work supported by NSF Grants OCE-0824612 and OCE-0825088.]

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.387

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.199
Teacher spread0.181 · 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 designObservational
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
Published2013
Admission routes1
Has abstractyes

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