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Record W2068550709 · doi:10.1117/12.718042

Electroactive polymer actuator online database

2007· article· en· W2068550709 on OpenAlexaff
John D. W. Madden, N. Genereux, K. A. Shkuratoff, Arjan van der Star, David Poon, Dave Irwin, Phoebe T. M. Cheng, Grace Hsu, Luca Filipozzi

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007
Typearticle
Languageen
FieldEngineering
TopicDielectric materials and actuators
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsActuatorComputer scienceInterface (matter)InterdependencePaceDatabaseVariety (cybernetics)Electroactive polymersArtificial intelligenceOperating system

Abstract

fetched live from OpenAlex

As polymer actuator performance improves there is an increasing demand to understand and compare properties. Past comparisons have relied on general statements of properties but do not capture the interdependence of these properties or keep up with the rapid pace of change. Modeling such interdependencies is complex. An alternative is to compile many measurements. A new actuator database has been created that is a compilation of experimental methods and results (mechanical, electrical, chemical and other properties) combined with a web interface. The objective is to capture actuator performance under a wide variety of conditions. The current content of the page is presented and justified. Researchers may submit data to the web page via an online form.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0010.000
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 head0.224
Teacher spread0.215 · 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 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

Citations4
Published2007
Admission routes1
Has abstractyes

Explore more

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