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Record W3094757511 · doi:10.1115/1.4049006

Balloon Locomotion for Extreme Terrain

2020· article· en· W3094757511 on OpenAlexafffund
Hari Nayar, Michael Pauken, Morgan L. Cable, Michael Hans, Manit Ginoya

Bibliographic record

VenueJournal of Mechanisms and Robotics · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of Ottawa
FundersUniversity of OttawaMitacsCalifornia Institute of TechnologyJet Propulsion LaboratoryNational Aeronautics and Space Administration
KeywordsTerrainTitan (rocket family)Software deploymentMars Exploration ProgramAerospace engineeringPayload (computing)Exploration of MarsAstrobiologyComputer scienceEnvironmental scienceMarine engineeringGeologySimulationEngineeringPhysicsGeography

Abstract

fetched live from OpenAlex

Abstract BALLET (BALloon Locomotion for Extreme Terrain) is a new concept vehicle for robotic surface mobility on planetary bodies with an atmosphere. The vehicle is composed of a buoyant balloon with six evenly distributed suspended payload modules each serving as a foot for locomotion over inaccessible rugged terrain. While the physics of BALLET will apply on Venus and Mars, the environmental conditions and available component technology limit our consideration to Titan. We describe the concept in detail, its applications for science missions on Titan, mission deployment scenarios, analyses of the concept under varying environmental conditions, and simulations of its locomotion. The concept is shown to be feasible and provides a new approach for exploration of rugged lakes, dunes, shorelines, and cryovolcanic regions on Titan.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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 communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.038
GPT teacher head0.229
Teacher spread0.191 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

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