MétaCan
Menu
Back to cohort
Record W4310731507 · doi:10.1063/5.0131733

I-LIFT (image-based laser-induced forward transfer) platform for manipulating encoded microparticles

2022· article· en· W4310731507 on OpenAlexaff
Sumin Lee, Wooseok Lee, Amos Chungwon Lee, Juhong Nam, JinYoung Lee, Hamin Kim, Yunjin Jeong, Huiran Yeom, Namphil Kim, Seo Woo Song, Sunghoon Kwon

Bibliographic record

VenueBiomicrofluidics · 2022
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsUniversity of Toronto
FundersChung Mong-Koo FoundationNational Research Foundation of Korea
KeywordsMicroparticleMultiplexingHomogeneousNanotechnologyLaserComputer scienceMicrofluidicsMultiplexMaterials sciencePhysicsBioinformaticsOpticsBiology

Abstract

fetched live from OpenAlex

Encoded microparticles have great potential in small-volume multiplexed assays. It is important to link the micro-level assays to the macro-level by indexing and manipulating the microparticles to enhance their versatility. There are technologies to actively manipulate the encoded microparticles, but none is capable of directly manipulating the encoded microparticles with homogeneous physical properties. Here, we report the image-based laser-induced forward transfer system for active manipulation of the graphically encoded microparticles. By demonstrating the direct retrieval of the microparticles of interest, we show that this system has the potential to expand the usage of encoded microparticles.

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 score0.372
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
Bibliometrics0.0000.001
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 head0.031
GPT teacher head0.250
Teacher spread0.219 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueBiomicrofluidicsSame topicInnovative Microfluidic and Catalytic Techniques InnovationFrench-language works237,207