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Record W2003810941 · doi:10.1678/rheology.32.253

Development of New Types of ER Fluid and Their Practical Application to Care and Rehabilitation Machines

2004· article· en· W2003810941 on OpenAlexaff
Akio Inoue, Isaburoh Fukawa, Ushio Ryu, Shigekazu Takenaka, Junji FURUSHO

Bibliographic record

VenueNihon Reoroji Gakkaishi · 2004
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsCasterClutchHomogeneousMaterials scienceBrakeType (biology)DiluentMechanical engineeringComposite materialEngineeringMetallurgyThermodynamicsPhysicsChemistry

Abstract

fetched live from OpenAlex

Asahi KASEI group developed two types of ER fluid and succeeded in employing them to practical applications. A homogeneous type consisting of liquid crystalline polysiloxane and a diluent was used for an intelligent brake in a caster walker which prevents a patient from stumbling. A heterogeneous (particle dispersion) type was used for a clutch in an upper limb training system with 3D movements and 3D vision. Key points for employing ER fluids in such devices with less trouble were introduced. The ER effect generation mechanisms of the homogeneous type fluids (type A and type B) were proposed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.282

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)0.0000.000

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 head0.009
GPT teacher head0.257
Teacher spread0.248 · 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.

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
Published2004
Admission routes1
Has abstractyes

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