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Record W2376843208 · doi:10.1016/0967-0653(95)99987-3

10.1016/0967-0653(95)99987-3

2000· article· en· W2376843208 on OpenAlexvenueno aff
Sun Fu

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsnot available
Fundersnot available
KeywordsSeries (stratigraphy)Moment (physics)Wind waveNonlinear systemRogue waveElevation (ballistics)Surface (topology)Statistical physicsDistribution (mathematics)Surface waveMathematicsMathematical analysisPhysicsGeologyClassical mechanicsGeometryOpticsQuantum mechanicsOceanography

Abstract

fetched live from OpenAlex

Based upon the nonlinear model of random sea waves,a commonly applicable statistical distribution of wave surface elevation exact to the third order is derived through the direct calculations of each order moment.The distribution arrived reduces,in the sense of being exact to H_6,to the Gram-Charlier series due to Longuet-Higgins for deep water,provided that only the two simplest kinds of wave-wave inter- actions are taken into account The reason why the agreement of Gram-Charlier series with experimental data becomes worse and worse as the terms of series are increased is explicited for the first time.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.010
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0030.004
Scholarly communication0.0050.007
Open science0.0040.004
Research integrity0.0070.003
Insufficient payload (model declined to judge)0.9900.993

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 head0.006
GPT teacher head0.151
Teacher spread0.145 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations11
Published2000
Admission routes1
Has abstractyes

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