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Record W2169262009 · doi:10.1109/vetec.1990.110300

An interactive train operations simulator for integrated applications in transit systems

2002· article· en· W2169262009 on OpenAlexafffund
Spencer McKay, V.I. John, G.E. Dawson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRailway Systems and Energy Efficiency
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBlock (permutation group theory)Computer scienceTrack (disk drive)SIGNAL (programming language)Set (abstract data type)Component (thermodynamics)SimulationWindow (computing)Real-time computingOperating systemProgramming language

Abstract

fetched live from OpenAlex

The enhancement of the Carnegie Mellon software package to incorporate fixed and moving-block signaling schemes is described. The train performance simulator (TPS) component of the module calculates the train dynamics for each train set in the simulation. For fixed-block signaling systems, the TPS monitors the preceding signal for each train and bases the train's calculations on that particular aspect, the type of signal, and whether a crossover is in the next block. Essentially, the aspects determine the local speed restrictions for each train. The aspects themselves are linked together, providing three and four block protection. Conversely, moving-block signaling systems would have train calculations based on the preceding train's dynamics, as opposed to fixed locations along the track. The TPS becomes interactive if signaling is invoked. A communications window is displayed at the bottom of the screen indicating the next aspect which the train is approaching.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.851
Threshold uncertainty score0.386

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 head0.013
GPT teacher head0.230
Teacher spread0.217 · 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 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".

Quick stats

Citations1
Published2002
Admission routes2
Has abstractyes

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