MétaCan
Menu
Back to cohort
Record W2096496784 · doi:10.1039/c3lc51170g

Large scale arrays of tunable microlenses

2013· article· en· W2096496784 on OpenAlex

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.

Bibliographic record

VenueLab on a Chip · 2013
Typearticle
Languageen
FieldEngineering
TopicElectrowetting and Microfluidic Technologies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsOblate spheroidOpticsFocal lengthDeformation (meteorology)Electric fieldMaterials scienceRange (aeronautics)ElectrodeSpheroidOptoelectronicsPhysicsLens (geology)ChemistryClassical mechanics

Abstract

fetched live from OpenAlex

We demonstrate a simple and robust method to produce large 2-dimensional and quasi-3-dimensional arrays of tunable liquid microlenses using a time varying external electric field as the only control parameter. With increasing frequency, the shape of the individual lensing elements (~40 μm in diameter) evolves from an oblate (lentil shaped) to a prolate (egg shaped) spheroid, thereby making the focal length a tunable quantity. Moreover, such microlenses can be spatially localized in desired configurations by patterning the electrode. This system has the advantage that it provides a large dynamic range of shape deformation (with a response time of ~30 ms for the whole range of deformation), which is useful in designing adaptive optics.

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 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: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.326

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 head0.004
GPT teacher head0.181
Teacher spread0.177 · 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