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Record W1824887011 · doi:10.24908/pceea.v0i0.4007

DESIGNING ARTIFICIAL MUSCLES: A BIOMIMETIC APPROACH

2011· article· en· W1824887011 on OpenAlexaffvenue
Sumitra Rajagopalan, Anatol G. Feldman, Julio Fernandes

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité de MontréalCentre Hospitalier Universitaire de Sherbrooke
Fundersnot available
KeywordsSelf-healing hydrogelsArtificial muscleIsotonicVinyl alcoholMaterials scienceContraction (grammar)DivalentBiophysicsChemical engineeringChemistryPolymer chemistryActuatorComposite materialComputer sciencePolymer

Abstract

fetched live from OpenAlex

This paper presents preliminary results of our ongoing work on the biomimetic muscle-like behaviour of poly(sodium acrylate) (PSA) hydrogels. Using Hill’s model as a basic framework, interpenetrating network (IPN) hydrogels consisting of a contractile PSA network and an elastic poly(vinyl alcohol) PVA network were desinged. The hydrogels so formed reversibly contract in the presence of a critical Ca2+ concentration via a monovalent-divalent ion exchange mechanism. Ca2+ is shown to provoke a shortening of the gel through cross-bridge formation akin to biological muscles. The contractile behaviour of these hydrogels in Krebs physiological media is presented. Force-length measurements display a non-linear rubber-like profile of the hydrogel in the relaxed state as well as a stiffening in the contracted state, both of which are characteristic of biological muscles. In addition, there is evidence of both isometric and isotonic contraction.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.018
GPT teacher head0.185
Teacher spread0.167 · 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

Citations1
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Canadian Engineering Education Association (CEEA)→Same topicAdvanced Sensor and Energy Harvesting Materials→French-language works237,207→