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Record W4285105512 · doi:10.1504/ijma.2022.10047304

Automated real-time 3D visual servoing control of single cell surgery with application to microinjection processes

2022· article· en· W4285105512 on OpenAlex
Bo Yao, James K. Mills

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

VenueInternational Journal of Mechatronics and Automation · 2022
Typearticle
Languageen
FieldEngineering
TopicPiezoelectric Actuators and Control
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPipetteMicroinjectionVisual servoingProcess (computing)AutomationComputer scienceComputer visionArtificial intelligenceEngineeringImage (mathematics)ChemistryBiologyCell biologyMechanical engineering

Abstract

fetched live from OpenAlex

Automating the cell surgery processes is a potential solution to eliminate human involvement and promote the development of cell surgery. Here, we propose a real-time 3D visual servocontrol system for single cell surgery with the experimental results of single cell injection of an embryo and analysis of experimental data. Real time 3D image processes are a necessary requirement since during cell surgery, when a micropipette contacts the embryo, the embryo is deformed, repositioning the internal components of the cell to be injected. An innovative 3D edge extraction algorithm is demonstrated for the real time 3D image processes. Visual servocontrol of the cell surgery process acquires the real-time target cell blastomere 3 dimensional position is used to maneuver the micropipette under real-time closed-loop feedback control. The automated embryo microinjection process is conducted using the proposed real-time 3D visual servocontrol system, which is proven to be a potential solution for microinjection automation.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.642
Threshold uncertainty score0.353

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 head0.002
GPT teacher head0.191
Teacher spread0.189 · 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