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Record W2041169744 · doi:10.1063/1.4721811

Red blood cell clustering in Poiseuille microcapillary flow

2012· article· en· W2041169744 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.

Bibliographic record

VenuePhysics of Fluids · 2012
Typearticle
Languageen
FieldMedicine
TopicBlood properties and coagulation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhysicsCluster (spacecraft)Hagen–Poiseuille equationMechanicsCluster analysisBiophysicsRed blood cellDrop (telecommunication)Flow (mathematics)Chemical physicsChemistryBiologyBiochemistryStatistics

Abstract

fetched live from OpenAlex

Red blood cells (RBC) flowing in microcapillaries tend to associate into clusters, i.e., small trains of cells separated from each other by a distance comparable to cell size. This process is usually attributed to slower RBCs acting to create a sequence of trailing cells. Here, based on the first systematic investigation of collective RBC flow behavior in microcapillaries in vitro by high-speed video microscopy and numerical simulations, we show that RBC size polydispersity within the physiological range does not affect cluster stability. Lower applied pressure drops and longer residence times favor larger RBC clusters. A limiting cluster length, depending on the number of cells in a cluster, is found by increasing the applied pressure drop. The insight on the mechanism of RBC clustering provided by this work can be applied to further our understanding of RBC aggregability, which is a key parameter implicated in clotting and thrombus formation.

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 score0.010
Threshold uncertainty score0.302

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 head0.018
GPT teacher head0.232
Teacher spread0.214 · 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