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Record W2031683385 · doi:10.1039/c2lc21210b

High-throughput biophysical measurement of human red blood cells

2012· article· en· W2031683385 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

VenueLab on a Chip · 2012
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsMount Sinai HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMicrofluidicsBiomedical engineeringElectrical impedanceRed blood cellMaterials scienceThroughputChemistryNanotechnologyMedicineComputer scienceBiochemistryElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

This paper reports a microfluidic system for biophysical characterization of red blood cells (RBCs) at a speed of 100-150 cells s(-1). Electrical impedance measurement is made when single RBCs flow through a constriction channel that is marginally smaller than RBCs' diameters. The multiple parameters quantified as mechanical and electrical signatures of each RBC include transit time, impedance amplitude ratio, and impedance phase increase. Histograms, compiled from 84,073 adult RBCs (from 5 adult blood samples) and 82,253 neonatal RBCs (from 5 newborn blood samples), reveal different biophysical properties across samples and between the adult and neonatal RBC populations. In comparison with previously reported microfluidic devices for single RBC biophysical measurement, this system has a higher throughput, higher signal to noise ratio, and the capability of performing multi-parameter measurements.

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 score0.056
Threshold uncertainty score0.503

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 head0.041
GPT teacher head0.270
Teacher spread0.229 · 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