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Record W2348798964

The Test Survey on the Acoustic Characteristic of Whistle For Locomotive

2000· article· en· W2348798964 on OpenAlexaboutno aff
Zheng Hong Tian

Bibliographic record

VenueRailway Occupational Safety, Health & Environmental Protection · 2000
Typearticle
Languageen
FieldEngineering
TopicVehicle Noise and Vibration Control
Canadian institutionsnot available
Fundersnot available
KeywordsFrench hornRADIUSTrack (disk drive)Degree (music)AcousticsSound (geography)PhysicsEngineeringComputer science
DOInot available

Abstract

fetched live from OpenAlex

Compare the acoustic characteristic with the different type of air horn.The measuring results showed that the air horn all produce 105~112 dB(A) of sound level at 30 meters directly in front of the train.2~8 dB(A)was happened at 30 meters radius subtended forward of the locomotive by angles 0 degree to the left or to the right of the centerline of the track in the forward direction of travel and 6~11 dB(A) was happened at 30 meters radius subtended forward of the locomotive by angles 0 degree and 90 degrees to the left or to the right of the centerline of the track in the forward direction of travel to the air horn of China.But 1~2 dB(A)was happened that whenever at 30 meters radius subtended forward of the locmotive by angles 0 degree or angles 0 degree and 90 degrees to the left or to the right of the centerline of the track in the forward direction of travel to the the air horn of U.S.A or Canada.The main sound energy of the air horn by the Canada or U.S.A.was appeared in from 250~4000 Hz,but the main sound energy of the ones by made in China was from 500~8000 Hz.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.239
Teacher spread0.218 · 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 designObservational
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
Published2000
Admission routes1
Has abstractyes

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Same venueRailway Occupational Safety, Health & Environmental ProtectionSame topicVehicle Noise and Vibration ControlFrench-language works237,207