MétaCan
Menu
Back to cohort
Record W2765902556 · doi:10.1109/oceanse.2017.8084847

Motion compensation of K-band radar ocean wave measurement

2017· article· en· W2765902556 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

VenueOCEANS 2017 - Aberdeen · 2017
Typearticle
Languageen
FieldEngineering
TopicRadar Systems and Signal Processing
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsRadarMotion compensationRemote sensingContinuous-wave radarGeodesyGeologyAcousticsRadar imagingComputer sciencePhysicsArtificial intelligenceTelecommunications

Abstract

fetched live from OpenAlex

Along with practicing the ocean wave measurement using K-band short-range radar, the impact of radar motion caused by a floating platform cannot be ignored. Radar motion needs to be compensated because the measurement method is based on sensing water particle motion which is apt to be influenced by radar motion. In this paper, motion compensation methods are proposed. Spectral difference method and mechanical method are designed to compensate linear motion and rotation motion respectively. The spectral difference method is evaluated using numerical simulation and then both of the two methods are validated in a wave tank. Wave period and height can be precisely measured in the numerical simulation and the wave tank experiment. The results prove that the radar motion impacts are successfully mitigated by the proposed motion compensation methods.

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 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 score0.323
Threshold uncertainty score0.574

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.047
GPT teacher head0.233
Teacher spread0.185 · 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