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Record W2000412604 · doi:10.1109/robot.2010.5509784

A micromanipulation system for single cell deposition

2010· article· en· W2000412604 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThroughputComputer scienceMicrofluidicsCellNanotechnologyComputer hardwareMaterials scienceChemistry

Abstract

fetched live from OpenAlex

Many microfabricated devices have been developed to quantify cellular response to a multitude of stimuli at a single-cell level in a high throughput manner. These single-cell studies require cells to be individually positioned at defined locations on a microdevice. This paper presents a micromanipulation system for automated pick-place of single cells. Integrating computer vision and motion control algorithms, the system visually tracks a cell in real time and controls multiple motion devices coordinately. Via fine manipulation of picoliter fluids and pressure of a few Pascals, the system accurately picks up a single cell, transfers the cell, and deposits it at a target location at a speed of 15-30 sec/cell. The micromanipulation system has the advantages of non-invasiveness, high specificity, and high precision. It is suitable to pick-place both non-labeled and labeled cells and applicable to standard cell culture substrates and microdevices with an open top.

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 score0.194
Threshold uncertainty score0.216

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 head0.010
GPT teacher head0.177
Teacher spread0.167 · 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

Quick stats

Citations39
Published2010
Admission routes2
Has abstractyes

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