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Record W2909689047 · doi:10.3390/rs11010096

Studies of Internal Waves in the Strait of Georgia Based on Remote Sensing Images

2019· article· en· W2909689047 on OpenAlexfundaboutno aff
Caixia Wang, Xin Wang, José C. B. da Silva

Bibliographic record

VenueRemote Sensing · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
FundersUniversity of British ColumbiaNational Natural Science Foundation of China
KeywordsInternal waveGeologyRemote sensingGeophysicsOceanography

Abstract

fetched live from OpenAlex

This paper analyzes over 500 sets of internal waves in the Strait of Georgia (British Columbia, Canada) based on a large number of satellite remote sensing images. The spatial and temporal distribution of internal waves in the central region of the strait are discussed via statistical analysis. Possible generation origins of the observed internal waves are divided into three categories based on their different propagation directions and geographical locations: (1) the interaction between the narrow channels to the south of the Strait and the tidal currents, leading to the formation of mainly eastward and northward propagating waves; (2) the interaction between the tidal currents and the topography near Point Roberts, resulting in mainly westward propagating waves; (3) excitation by river plume, mainly near Fraser River mouth, leading to the formation of mainly westward waves along the direction of the river plume. The relation between the occurrence of internal waves in remote sensing images and wind or tide level is also discussed. It is found that most of the observed internal waves occur at low tides. However, due to the influence of the river, the eastward propagating internal waves near the river mouth seldom occur at the lowest tide. Also, internal waves are captured more easily by remote sensing images in summer due to the lower wind speed than winter and therefore the seasonal distribution of internal waves in remote sensing images may not be able to completely represent the real situation in the study area. Finally, combining the in situ measured data and model output data, the Benjamin-Ono equation is found to satisfyingly simulate the characteristic parameters of the studied internal waves.

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 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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.016
GPT teacher head0.239
Teacher spread0.223 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations21
Published2019
Admission routes2
Has abstractyes

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