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Record W3080294544 · doi:10.1117/12.2570444

Light-driven microrobotics and their applications for single-cell manipulation

2020· article· en· W3080294544 on OpenAlexaff
Shuailong Zhang, Aaron R. Wheeler

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Micro-robotics is exploding in popularity, driven by the need to control the position of individual cells and other micronsized particles. There are many examples of optical tweezer-based micro-robots; here we introduce the first microrobotic system that relies on the related technology of optoelectronic tweezers (OET). The optoelectronic micro-robots described here are straightforward to manufacture and can be programmed to carry out sophisticated, multi-axis operations. One particularly useful program is a serial combination of “load,” “transport,” and “deliver,” which can be applied to manipulate a wide range of micron-dimension payloads. Importantly, micro-robots programmed in this manner are much gentler on fragile mammalian cells than conventional OET techniques. The micro-robotic system described here was demonstrated to be useful for single-cell isolation, clonal expansion and RNA sequencing, applications that are becoming increasingly important in the post-CRISPR life-science research landscape. We propose that the OET micro-robotic system, which can be implemented using a microscope and consumer-grade optical projector, will be useful for a wide range of applications in the life sciences and beyond.

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)0.000
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: Methods · Consensus signal: none
Teacher disagreement score0.976
Threshold uncertainty score0.282

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 head0.028
GPT teacher head0.224
Teacher spread0.195 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations6
Published2020
Admission routes1
Has abstractyes

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