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Record W4381186309 · doi:10.11159/cdsr23.004

A Design-thinker for Design of Soft Robots

2023· article· en· W4381186309 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.

Bibliographic record

VenueProceedings of the International Conference of Control, Dynamic systems, and Robotics · 2023
Typearticle
Languageen
FieldEngineering
TopicModular Robots and Swarm Intelligence
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsRobotComputer scienceHuman–computer interactionArtificial intelligence

Abstract

fetched live from OpenAlex

Soft robots have been found many applications in medicine and in service operations.However, the contemporary philosophy in designing soft robots is to go along with bio-mimics.That is, design and building of engineered systems to possess the special capability of creatures or animals.This design philosophy has a limit, because the system so built will not go beyond the creature.In this talk, the author will propose a new design philosophy for building soft robots, which advocates the engineering design process to design and to build a soft robot.More specifically, the design process for soft robots will begin with understanding and analyzing requirements for a soft robot under design and building, and then go along with the phases of concept design, embodiment design and detail design.The special capability of creatures may be incorporated into these design phases.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.474

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.045
GPT teacher head0.249
Teacher spread0.204 · 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