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Record W13676843

Intelligent Mobility: An Assessment of Past and Present UGV Concepts at DRDC Suffield

2003· article· en· W13676843 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueZhurnal mikrobiologii epidemiologii i immunobiologii · 2003
Typearticle
Languageen
FieldEngineering
TopicSimulation and Modeling Applications
Canadian institutionsnot available
Fundersnot available
KeywordsUnmanned ground vehicleExploitTerrainSurvivabilityObstacleAxleTraverseComputer scienceEmbedded systemSimulationEngineeringArtificial intelligenceComputer securityComputer network
DOInot available

Abstract

fetched live from OpenAlex

Abstract : The Tactical Vehicle System Section (TVSS) of Defence R&D Canada- Suffield (DRDC Suffield) conducts research to exploit the potential of Unmanned Ground Vehicles (UGVs) for increasing soldier survivability and mobility. UGV mobility is one area of concern. Intelligent mobility describes the ability of an unmanned ground vehicle to traverse unstructured, obstacle-ridden terrain successfully with limited or less discriminating perception and simplified control. This paper provides an assessment of the intelligent mobility of an emerging concept compared to four previous UGV platforms developed for/by DRDC Suffield. It describes the SAAS (Solid Axle Ackerman Steered) UGV concept in terms of its hardware configuration, control hardware requirements, and attendant mobility performance. The SAAS will exhibit superior performance for UGV operations and roles.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.057
GPT teacher head0.375
Teacher spread0.318 · 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