MétaCan
Menu
Back to cohort
Record W4395484779 · doi:10.1117/12.3002808

Development of a label-free optofluidic platform based on quantitative-phase digital holographic microscopy and microfluidics to perform biophysical phenotyping of human cells

2024· article· en· W4395484779 on OpenAlexaff
Erik Bélanger, Gabrielle Jess, Céline Larivière-Loiselle, Sara Mattar, Niraj Patel, Zahra Yazdani-Najafabadi, Mohamed Haouat, Johan Chaniot, Émile Rioux-Péllerin, Marie‐Ève Crochetière, Jean-Xavier Giroux, Antoine Allard, Patrick Desrosiers, Pierre Marquet

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDigital Holography and Microscopy
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMicrofluidicsDigital holographic microscopyHolographyMicroscopyPhase imagingDigital holographyDigital microfluidicsNanotechnologyComputer sciencePhase (matter)Materials scienceOptoelectronicsOpticsChemistryPhysics

Abstract

fetched live from OpenAlex

Progress achieved in the field of stem-cell technology allows the reprogramming of patient-derived cells, obtained from urine or skin biopsies, into induced pluripotent stem cells that can then be differentiated into any cell types. Within this framework, techniques, being able to accurately and non-invasively characterize cell structure, morphology, and dynamics, represent very promising approaches to identify disease-specific cell phenotypes. Consequently, we will present how a label-free optofluidic platform, based on quantitative-phase digital holographic microscopy along with various experimental developments in microfluidics, constitutes a very appealing cell imaging methodology to identify, through the measurement of biophysical properties, specific cell phenotypes.

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 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 score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.316
Teacher spread0.292 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicDigital Holography and MicroscopyFrench-language works237,207