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Record W1510613245

Application of Surface Sound Speed Measurements in Post-processing for Multi-Sector Multibeam Echosounders

2004· article· en· W1510613245 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueUniversity of New Hampshire Scholars Repository (University of New Hampshire at Manchester) · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsCanadian Hydrographic ServiceUniversity of New Brunswick
Fundersnot available
KeywordsSonarDepth soundingSynthetic aperture sonarRange (aeronautics)Mode (computer interface)Computer scienceAcousticsRemote sensingData processingReal-time computingGeologyEngineeringArtificial intelligenceAerospace engineeringOceanographyPhysics
DOInot available

Abstract

fetched live from OpenAlex

Given sufficient data from ancillary sensors, swath sonar systems can generate sounding solutions in real time. The absolute accuracy o f these solutions depends both on the sonar-relative range and angle determination, and particularly on the quality of the aiding information. In this paper, we examine the correction of imperfect surface sound speed information for a multi-sector swath sonar. Difficulties arise from: (1) sector timings and boundaries changing with operational mode, and (2) insufficient information to determine the transmit sector associated with a receive beam. A number of post-processing strategies are proposed and the specific steps in implementation are described in detail.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.072
GPT teacher head0.251
Teacher spread0.179 · 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