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Record W4407173785 · doi:10.1002/adfm.202570035

Programmable Shape‐Preserving Soft Robotics Arm via Multimodal Multistability (Adv. Funct. Mater. 6/2025)

2025· article· en· W4407173785 on OpenAlexaff
Benyamin Shahryari, Hossein Mofatteh, Arian Sargazi, Armin Mirabolghasemi, David Meger, Abdolhamid Akbarzadeh

Bibliographic record

VenueAdvanced Functional Materials · 2025
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsSoft roboticsMultistabilityMaterials scienceRoboticsNanotechnologyArtificial intelligenceComputer scienceRobotPhysics

Abstract

fetched live from OpenAlex

Programmable Multimodal Multistable Metamaterials The cover art depicts symbolized figures in a peaceful garden that demonstrate how shape-changing mechanical metamaterials can be integrated into advanced robotic arms for daily life applications. These arms, based on multimodal multistable unit cells, preserve alternate configurations without requiring power while supporting significant loads. In article number 2407651, Abdolhamid Akbarzadeh and co-workers introduce programmable arms with precise deformation control through a pneumatic actuator, reflecting their applications in soft robotics. Cover by SciFig (https://sci-fig.com/).

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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.556
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.244
Teacher spread0.231 · 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 teacher head, not a consensus.

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
Published2025
Admission routes1
Has abstractyes

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