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Record W2323307426 · doi:10.2208/kaigan.70.i_356

Numerical Experiment on Observation Capabilities of Oceanographic Radar on Far Field and Near Field Tsunamis

2014· article· en· W2323307426 on OpenAlexaboutno aff
Megumi Okamoto, Shuji Seto, Tomoyuki Takahashi, H. Hinata

Bibliographic record

VenueJournal of Japan Society of Civil Engineers Ser B2 (Coastal Engineering) · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeologySeismologyRadarPeninsulaNear and far fieldField (mathematics)Tsunami waveGeographyEngineeringTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

Two oceanographic Radars targeting tsunamis had been installed in Wakayama Prefecture in Japan. To study observation capabilities of the radars on far field and near field tsunamis, numerical experiments were carried out. After starting the operation of the radars, nine earthquakes occurred in the observation area, however, they were too small to be observed by the radars. Parameter study on near field tsunamis showed the radars can observe earthquake of Mw 7 and very shallow Mw 6. As a far field tsunami, the 2012 Haida Gweii Earthquake Tsunami arrived at Japan, however, the radars could not detect it because of very small velocity. Parameter study on far field tsunamis showed the main energy of tsunamis off Canada propagates northward, and Oshika Peninsula is suitable to observe the tsunamis.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.190
Teacher spread0.181 · 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 designSimulation or modeling
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
Published2014
Admission routes1
Has abstractyes

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Same venueJournal of Japan Society of Civil Engineers Ser B2 (Coastal Engineering)Same topicearthquake and tectonic studiesFrench-language works237,207