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Record W2314611543 · doi:10.1021/am505140f

Magnetic Field Switchable Dry Adhesives

2015· article· en· W2314611543 on OpenAlex
Jeffrey Krahn, Enrico Bovero, Carlo Menon

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACS Applied Materials & Interfaces · 2015
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAdhesionMaterials scienceAdhesiveMagnetic fieldPaint adhesion testingComposite materialStiffnessPreloadNuclear magnetic resonance

Abstract

fetched live from OpenAlex

A magnetic field controllable dry adhesive device is manufactured. The normal adhesion force can be increased or decreased depending on the presence of an applied magnetic field. If the magnetic field is present during the entire normal adhesion test cycle which includes both applying a preloading force and measuring the pulloff pressure, a decrease in adhesion is observed when compared to when there is no applied magnetic field. Similarly, if the magnetic field is present only during the preload portion of the normal adhesion test cycle, a decrease in adhesion is observed because of an increased stiffness of the magnetically controlled dry adhesive device. When the applied magnetic field is present during only the pulloff portion of the normal adhesion test cycle, either an increase or a decrease in normal adhesion is observed depending on the direction of the applied magnetic field.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.026
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)0.0010.001

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 head0.014
GPT teacher head0.222
Teacher spread0.208 · 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