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Record W2160029619 · doi:10.5555/1161734.1162067

Air cargo operations evaluation and analysis through simulation

2004· article· en· W2160029619 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueWinter Simulation Conference · 2004
Typearticle
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsAir CanadaCarleton University
Fundersnot available
KeywordsComputer scienceWork (physics)Air cargoControl (management)Set (abstract data type)Systems engineeringOperations researchRisk analysis (engineering)Process managementTransport engineeringEngineeringBusiness

Abstract

fetched live from OpenAlex

This paper illustrates the use of simulation for evaluating and analyzing air cargo operations at one of the new state-of-the art cargo facilities at Toronto Pearson Airport. The establishment of a facility equipped with some of the latest in modern material handling systems available today and a computerized-based inventory control system that interfaces with all aspects of its cargo operations, has driven the airline company involved in this study to developing new processes to ensure that products and services are aligned with customers' needs. One of the challenges faced is a lack of an evaluation tool that can be used to quantitatively evaluate and compare different policies, business practices and processes within a given set of operational and business constraints. This work aims in developing such an evaluation tool. We describe the modeling approach, the challenges involved and the potential use of the simulation tool. Preliminary results are also reported.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.759
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.232
GPT teacher head0.489
Teacher spread0.258 · 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