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Record W4414290624 · doi:10.1088/978-0-7503-6478-2ch3

Sound waves (longitudinal waves)

2025· book-chapter· en· W4414290624 on OpenAlexaff
Pradeep Sharma

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsCanadian Association of Physicists
Fundersnot available
KeywordsLongitudinal waveSuperposition principleSound (geography)Particle displacementSound intensityStanding waveMechanical waveAcoustic waveLoudness

Abstract

fetched live from OpenAlex

In a longitudinal wave, particles move along the line of wave propagation. Sound waves are longitudinal waves. As sound wave travels through air in the form of compression and dilations of air. A tuning fork can produce harmonic pressure waves. In this chapter the generation, transmission, reflection, superposition (interference, stationary wave and beats), the difference between the pitch, intensity and loudness of sound etc, of longitudinal waves are described. You will learn the resonant longitudinal standing waves in organ pipes. At the end, you will learn the Doppler’s effect as a consequence of relative motion between the source and observer.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.089
Threshold uncertainty score0.299

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0890.056

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 head0.044
GPT teacher head0.263
Teacher spread0.219 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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