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Record W1968924314 · doi:10.1038/srep05374

Seismic, satellite and site observations of internal solitary waves in the NE South China Sea

2014· article· en· W1968924314 on OpenAlexaff
Qunshu Tang, Caixia Wang, Dongxiao Wang, Rich Pawlowicz

Bibliographic record

VenueScientific Reports · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsUniversity of British Columbia
FundersNorthwest Fisheries Science CenterNational Natural Science Foundation of China
KeywordsSatelliteChinaSeismologyGeologyGeodesyRemote sensingGeographyAstronomyPhysicsArchaeology

Abstract

fetched live from OpenAlex

Internal solitary waves (ISWs) in the NE South China Sea (SCS) are tidally generated at the Luzon Strait. Their propagation, evolution, and dissipation processes involve numerous issues still poorly understood. Here, a novel method of seismic oceanography capable of capturing oceanic finescale structures is used to study ISWs in the slope region of the NE SCS. Near-simultaneous observations of two ISWs were acquired using seismic and satellite imaging, and water column measurements. The vertical and horizontal length scales of the seismic observed ISWs are around 50 m and 1-2 km, respectively. Wave phase speeds calculated from seismic observations, satellite images, and water column data are consistent with each other. Observed waveforms and vertical velocities also correspond well with those estimated using KdV theory. These results suggest that the seismic method, a new option to oceanographers, can be further applied to resolve other important issues related to ISWs.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.018
GPT teacher head0.199
Teacher spread0.180 · 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

Citations30
Published2014
Admission routes1
Has abstractyes

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