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Record W2552892684 · doi:10.3103/s1068371216090042

On statistical models of the amplitude and the duration of pulsed electromagnetic interference in automatic-control and telemechanic channels of subway lines

2016· article· en· W2552892684 on OpenAlex
P. F. Bestem’yanov, I. G. Gorlin

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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".

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

VenueRussian Electrical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicRailway Systems and Energy Efficiency
Canadian institutionsBombardier (Canada)
Fundersnot available
KeywordsAmplitudeStandard deviationInterference (communication)Electromagnetic interferenceMathematicsProbability density functionTrainMathematical analysisElectromagnetic compatibilityPulse durationAcousticsControl theory (sociology)Electronic engineeringPhysicsComputer scienceEngineeringStatisticsElectrical engineeringOptics

Abstract

fetched live from OpenAlex

On the basis of the results of experimental studies of the interference from the traction current of subway trains, the distribution type of this interference has been established. Approximation of experimental data by an analytical expression based on the Pearson curve family underlies the proposed method. The approximation is performed by calculating the first four distribution moments. The common array of the initial data on the electromagnetic interference is divided into two parts, depending on the type of the rolling stock—either with the switched-on-off tracking regenerative-rheostatic braking system or without it. The 7‒10-min recordings of the data on the traction current for trains with or without regenerative braking have been processed. To normalize the experimental data, the mathematical expectation estimate is subtracted from the former and the obtained values are divided by the estimate of the standard deviation. The resulting new data array has normalized properties, i.e., the zero mathematical expectation and a unit standard deviation. Then, from the normalized data array, the first four sampling moments are found, on the basis of which the corresponding Pearson curve is selected. The method underlies the estimation of the distribution density of the pulsed interference amplitude and the duration of the electromagnetic interference pulses. It has been shown that, in all 12 frequency ranges from 50 to 780 Hz that are used in subway automatic control and telemechanical devices, the distribution density of the pulsed interference amplitude and the interference pulse duration can be described by the analytical expression of the β-distribution of the first and second kind.

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 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score0.264

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 communication0.0000.000
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 head0.004
GPT teacher head0.172
Teacher spread0.169 · 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