MétaCan
Menu
Back to cohort
Record W4232165056 · doi:10.1089/soro.2016.0043

Arthrobots

2017· article· en· W4232165056 on OpenAlexfundno aff
Alex Nemiroski, Yanina Shevchenko, Adam A. Stokes, Barış Ünal, Alar Ainla, Sahradha Albert, Gabrielle Compton, Emily Macdonald, Yosyp Schwab, Caroline Zellhofer, George M. Whitesides

Bibliographic record

VenueSoft Robotics · 2017
Typearticle
Languageen
FieldEngineering
TopicModular Robots and Swarm Intelligence
Canadian institutionsnot available
FundersDivision of Materials ResearchNatural Sciences and Engineering Research Council of CanadaDefense Advanced Research Projects AgencyNational Science FoundationVetenskapsrådetHansjörg Wyss Institute for Biologically Inspired Engineering, Harvard UniversityHarvard UniversityNorthwestern UniversityU.S. Department of Energy
KeywordsInflatableCrawlingExoskeletonRobotSlippageComputer scienceStructural engineeringMechanical engineeringEngineeringSimulationArtificial intelligenceAnatomy

Abstract

fetched live from OpenAlex

This article describes a class of robots-"arthrobots"-inspired, in part, by the musculoskeletal system of arthropods (spiders and insects, inter alia). Arthrobots combine mechanical compliance, lightweight and simple construction, and inexpensive yet scalable design. An exoskeleton, constructed from thin organic polymeric tubes, provides lightweight structural support. Pneumatic joints modeled after the hydrostatic joints of spiders provide actuation and inherent mechanical compliance to external forces. An inflatable elastomeric tube (a "balloon") enables active extension of a limb; an opposing elastic tendon enables passive retraction. A variety of robots constructed from these structural elements demonstrate (i) crawling with one or two limbs, (ii) walking with four or six limbs (including an insect-like triangular gait), (iii) walking with eight limbs, or (iv) floating and rowing on the surface of water. Arthrobots are simple to fabricate and are able to operate safely in contact with humans.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0490.034

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 head0.023
GPT teacher head0.246
Teacher spread0.222 · 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 designBench or experimental
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

Citations88
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueSoft RoboticsSame topicModular Robots and Swarm IntelligenceFrench-language works237,207