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Record W2967416250 · doi:10.1109/tmech.2019.2935181

Consistent Manufacturing Device for Coiled Polymer Actuators

2019· article· en· W2967416250 on OpenAlexaff
Sarah A. Horton, Patrick Dumond

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsActuatorMaterials scienceMechanical engineeringPredictabilityProtein filamentPolymerComputer scienceComposite materialEngineeringArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

Coiled polymer actuators are fabricated by heating a twisted nylon fishing filament. This paper provides a detailed review of their manufacturing process and proposes a method which manufactures these actuators consistently to improve the predictability of their behavior. Two devices are presented: a device that prepares consistent filament sections, and another that twists and coils the filament. Seven successful actuators are produced using the proposed method and compared with seven actuators produced using a method featured in other studies. The behavior of both sets of actuators is then compared using tensile tests on an Instron universal testing machine. The actuators manufactured using the device demonstrate a lower fail rate and produce more force on average. However, the average force produced by each actuator using the proposed method varied slightly. It is believed this fluctuation is due to inconsistent resistance wire lengths and the actuator end loop creation technique. Both of which would require additional improvement.

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)0.002
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.214
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

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

Citations13
Published2019
Admission routes1
Has abstractyes

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