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Gap-less Bilateral Swath Bathymetry

2021· article· en· W4213225004 on OpenAlexaff
А.В. Иванов, Caleb MacDonald

Bibliographic record

VenueOCEANS 2021: San Diego – Porto · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsMetamaterial Technologies (Canada)
Fundersnot available
KeywordsBathymetrySonarGeologyUnderwaterNadirSide-scan sonarRemote sensingPort (circuit theory)AcousticsGeodesyEngineeringOceanographyPhysics

Abstract

fetched live from OpenAlex

Side scan sonars commonly encounter large gaps in the nadir region, without a convenient way to compensate for the lost area. Likewise, swath bathymetric sonars collect 3D images to both sides of the sonar but cannot connect the two sides of the image without missing data, therefore effectively reducing bilateral swath to unilateral. Described is a novel bilateral swath bathymetry system and method with angled fan-shaped beams for a gapless 3-D reconstruction of the sea bottom scene on port, starboard and in front of the underwater vehicle without incurring data losses in the nadir area. The sonar system contains two angled forward port and starboard interferometric acoustic arrays, each transmitting a fan-shaped beam and measuring the angles of arrival of the returned echoes with spaced acoustic elements.

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: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.030
GPT teacher head0.256
Teacher spread0.225 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueOCEANS 2021: San Diego – PortoSame topicUnderwater Acoustics ResearchFrench-language works237,207