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Record W2099557702 · doi:10.1109/icmens.2003.1222026

A microfluidic device with on-chip optical waveguide interrogation of individual biological cells for medical diagnostics

2004· article· en· W2099557702 on OpenAlexaff
Kamal Deep Singh, C. Liu, C. E. Capjack, W. Rozmus, C. Backhouse

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMicrofluidicsMicrofluidic chipWaveguideOrganelleOptoelectronicsMitochondrionMaterials scienceCancer cellChipLab-on-a-chipNanotechnologyComputer scienceCancerBiologyCell biologyTelecommunications

Abstract

fetched live from OpenAlex

We present a microfluidic device for on-chip optical analysis and characterisation of biological cells. We employ a novel waveguiding technique for detection and analysis of the cells. This waveguiding technique is particularly well suited to this since a number of unique characteristics of the optical waveguide come together to enable detailed analysis of the very low level of scattered light. We are interested in the analysis and characterisation of sub-wavelength features such as nuclei and mitochondria within living cells. Such nanoscale probing of intracellular matter promises to offer reliable diagnostic procedures for biological cells. Of particular interest are the mitochondria, since the size and number of these can provide useful information as to the health of the cell. Mitochondria are the organelles in which energy production takes place, and as such are of vital importance. Mitochondrial abnormalities are often associated with serious diseases including cancer.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.234
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2004
Admission routes1
Has abstractyes

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