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Record W2144095297 · doi:10.1109/iros.2007.4399569

Development of a five degree-of-freedom biomanipulator for autonomous single cell electroporation

2007· article· en· W2144095297 on OpenAlexaff
Kell Sakaki, Nikolai Dechev, Edward J. Park, Robert D. Burke

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMicroinjectionThroughputElectroporationFlexibility (engineering)Computer scienceAutomationDegrees of freedom (physics and chemistry)Artificial intelligenceBiomedical engineeringBiologyCell biologyEngineeringMathematicsMechanical engineering

Abstract

fetched live from OpenAlex

Studies of individual cells via microscopy and microinjection are a key component in research on gene functions, cancer, stem cells, and reproductive technology. As biomedical experiments become more complex, there is an urgent need for robotic systems to: improve cell manipulation, increase throughput, reduce lost cells, and improve reaction detection. Automation of these tasks using visual servoing creates significant benefits for biomedical laboratories including repeatability of experiments, higher throughput, and a controlled environment capable of operating 24 hours a day. In this work the design and development of a new five degree-of- freedom biomanipulator designed for single-cell microinjection, is described. The biomanipulator employs three degrees of linear motion and two degrees of rotation. This provides the ability to manipulate/micro-inject cells at varying orientations, thereby increasing flexibility in dealing with complex operations such as injecting clustered cells. The capability of the biomanipulator is shown with preliminary experimental results using mouse myeloma cells.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.325

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 head0.030
GPT teacher head0.222
Teacher spread0.193 · 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
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

Citations13
Published2007
Admission routes1
Has abstractyes

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