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Record W2078760931 · doi:10.1287/ijoc.2014.0604

Computing the Distribution for the Number of Renewals with Bulk Arrivals

2014· article· en· W2078760931 on OpenAlex

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

VenueINFORMS journal on computing · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicScientific Research and Discoveries
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsLaplace transformExtension (predicate logic)MathematicsApplied mathematicsDistribution (mathematics)Laplace distributionMapleDiscrete time and continuous timeLaplace's methodWork (physics)Mathematical optimizationMathematical analysisComputer scienceStatistics

Abstract

fetched live from OpenAlex

The distribution of the number of renewals for bulk arrivals in continuous time is calculated using an algorithm employed through MAPLE software. These numerical results are acquired by considering rational as well as nonrational Laplace transforms and Padé-approximated Laplace transforms for the distributions of interrenewal times. Further, through the use of Laplace transforms an elegant solution to determine the asymptotic results for the first and second moments of the number of bulk renewals is presented. These derivations help validate the numerical results and are an extension of previous work by the authors regarding single-arrival renewal theory in discrete time.

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.

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)0.002
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 score0.599
Threshold uncertainty score0.637

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.016
GPT teacher head0.302
Teacher spread0.286 · 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