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Record W2035634293 · doi:10.1016/j.procs.2013.06.116

Freight Market Interactions Simulation (FREMIS): An Agent-based Modeling Framework

2013· article· en· W2035634293 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

VenueProcedia Computer Science · 2013
Typearticle
Languageen
FieldEngineering
TopicUrban and Freight Transport Logistics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceScope (computer science)Focus (optics)Conceptual frameworkRationalityAgent-based modelProduct (mathematics)Presentation (obstetrics)Conceptual modelOperations researchArtificial intelligenceDatabase

Abstract

fetched live from OpenAlex

Freight modeling frameworks are frequently based on passenger modeling approaches. Comprehensive and specific freight modeling frameworks are required to improve the evaluation of freight related policies. In this paper, a new agent-based freight modeling framework is presented which is able to incorporate important elements in modern freight markets: agent interactions, product differentiation and economies of scope/scale. These elements are combined in a market dynamic environment assuming agent rationality and that agents acquire information while interacting with each other. The conceptual presentation of this framework is the focus of this paper and the data required for its implementation is also discussed.

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)0.000
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: Methods · Consensus signal: none
Teacher disagreement score0.776
Threshold uncertainty score0.584

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 communication0.0000.001
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 head0.031
GPT teacher head0.237
Teacher spread0.206 · 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