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Record W1593661961 · doi:10.1002/9781118856024.ch10

Internal Waves in Laboratory Experiments

2014· other· en· W1593661961 on OpenAlex
Bruce Sutherland, Thierry Dauxois, Thomas Peacock

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

VenueGeophysical monograph · 2014
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInternal waveSchlierenInviscid flowRotational symmetryParticle image velocimetryPhysicsSchlieren photographyPerturbation (astronomy)Schlieren imagingVelocimetryMechanicsAcousticsOpticsFlow visualization

Abstract

fetched live from OpenAlex

This chapter focuses mostly upon the use of synthetic schlieren to measure perturbation density gradients due to internal waves in continuously stratified media. When used to examine spanwise-uniform and axisymmetric disturbances, it has provided a useful check on the limitations of linear, inviscid theory. The chapter reviews an analysis method for separating out waves propagating in different directions, and describes a recently developed mechanism for generating waves that does not suffer some of the drawbacks of oscillating or towed rigid objects. It briefly discusses how synthetic schlieren visualizes disturbances in a fluid through contrasting snapshots taken by a digital camera looking through the fluid at a black-and-white image of lines or dots. The chapter describes the treatment of axisymmetric and fully three-dimensional disturbances. Finally, other advances in generating internal waves and analyzing them using particle image velocimetry (PIV) are described.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.834
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.204
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