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Record W2132728162 · doi:10.1504/ijlsm.2010.032943

A bi-level representational model of hazardous material supply chains

2010· article· en· W2132728162 on OpenAlex
Nathalie de Marcellis-Warin, Martin Trépanier, Sébastien Favre

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

VenueInternational Journal of Logistics Systems and Management · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsSupply chainRepresentation (politics)IntermediaryHazardous wasteComputer scienceSupply chain managementBusinessIndustrial organizationRisk analysis (engineering)Marketing

Abstract

fetched live from OpenAlex

Modelling the transportation and storage tasks associated with supply chains is usually based on a tacit or mathematical representation of physical flows. However, remaining at this level of representation seems inadequate for risk management. This study proposes to insert new graphical tools into the models to improve the representation of hazardous material supply chains. This representational model enables us to show physical flows and contractual flows at the same time, and highlights the responsibility interactions and risk transfers among the numerous stakeholders involved: producers, carriers, storage enterprises, intermediaries and consumers.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.832
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.033
GPT teacher head0.262
Teacher spread0.229 · 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