MétaCan
Menu
Back to cohort
Record W2046852349 · doi:10.1175/jpo-d-12-0237.1

Wave Breaking Dissipation in a Young Wind Sea

2013· article· en· W2046852349 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

VenueJournal of Physical Oceanography · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsUniversity of Victoria
FundersAchievement Rewards for College Scientists FoundationUniversity of WashingtonNational Science Foundation
KeywordsBreaking waveDissipationSwellPhysicsCrestGeologyWind waveMechanicsMeteorologyWave propagationOpticsOceanography

Abstract

fetched live from OpenAlex

Abstract Coupled in situ and remote sensing measurements of young, strongly forced wind waves are applied to assess the role of breaking in an evolving wave field. In situ measurements of turbulent energy dissipation from wave-following Surface Wave Instrument Float with Tracking (SWIFT) drifters and a tethered acoustic Doppler sonar system are consistent with wave evolution and wind input (as estimated using the radiative transfer equation). The Phillips breaking crest distribution Λ(c) is calculated using stabilized shipboard video recordings and the Fourier-based method of Thomson and Jessup, with minor modifications. The resulting Λ(c) are unimodal distributions centered around half of the phase speed of the dominant waves, consistent with several recent studies. Breaking rates from Λ(c) increase with slope, similar to in situ dissipation. However, comparison of the breaking rate estimates from the shipboard video recordings with the SWIFT video recordings show that the breaking rate is likely underestimated in the shipboard video when wave conditions are calmer and breaking crests are small. The breaking strength parameter b is calculated by comparison of the fifth moment of Λ(c) with the measured dissipation rates. Neglecting recordings with inconsistent breaking rates, the resulting b data do not display any clear trends and are in the range of other reported values. The Λ(c) distributions are compared with the Phillips equilibrium range prediction and previous laboratory and field studies, leading to the identification of several inconsistencies.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.304

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 communication0.0000.001
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 head0.009
GPT teacher head0.206
Teacher spread0.198 · 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