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Record W4405760309 · doi:10.4006/0836-1398-37.4.305

Investigation on the transverse Doppler effect

2024· article· en· W4405760309 on OpenAlexvenueno aff
Xing-Bin Huang

Bibliographic record

VenuePhysics Essays · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Frequency and Time Standards
Canadian institutionsnot available
Fundersnot available
KeywordsTransverse planeTime dilationPhysicsDoppler effectBlueshiftOpticsTransverse wavePlane (geometry)Special relativityQuantum electrodynamicsTheory of relativityClassical mechanicsQuantum mechanicsWave propagationGeometry

Abstract

fetched live from OpenAlex

The widely accepted viewpoint asserts that the transverse Doppler effect for plane light waves is a red shift, a purely relativistic effect caused by the time dilation or the slowing down of a moving clock. However, rigorous proof for the assertion is absent in available literature. Here, we investigated the transverse Doppler shifts for plane and spherical waves. The results show that for plane light waves, the red shift may not be a purely relativistic effect, and the true transverse Doppler effect might be a blue shift, which might mean that a moving clock can also run faster than an identical clock at rest. For spherical light waves, the transverse Doppler effect is a blue shift when a source is at the center of a rotating disk and the receiver is at its rim; on the contrary, it is a red shift. The results might not only reflect new features of special relativity but also benefit physics teaching.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.022
GPT teacher head0.255
Teacher spread0.233 · 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 designBench or experimental
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
Published2024
Admission routes1
Has abstractyes

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