MétaCan
Menu
Back to cohort
Record W163796348 · doi:10.5555/1999416.1999420

Modeling and analysis of Canadian forces RSOM hubs for northern operations

2010· article· en· W163796348 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

VenueSummer Computer Simulation Conference · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFacility Location and Emergency Management
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsSoftware deploymentLift (data mining)Computer scienceOperations researchOperations managementEngineeringData mining

Abstract

fetched live from OpenAlex

This paper presents an analysis of a Reception, Staging and Onward Movement (RSOM) hub concept to support Canadian Forces (CF) Northern operations. RSOM hubs are permanent or temporary staging bases for cross-loading between strategic and tactical lift during military deployment and sustainment operations. Performance measures were developed to assess the effectiveness and the responsiveness of different hub options. An optimization model was also developed to determine the optimal number and locations of hubs. Deployment scenarios to different Northern locations were simulated and assessed. Sensitivity analysis was conducted to examine the impact of different operational parameters on hub performance. The study indicated that the RSOM hub concept would offer potential cost avoidance and response time reduction on deployment lift for Northern operations and could be a potential strategy for improvement of the CF domestic support capability.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.063
GPT teacher head0.270
Teacher spread0.207 · 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