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Record W1987698311 · doi:10.1063/1.4867035

Quantifying the volume of single cells continuously using a microfluidic pressure-driven trap with media exchange

2014· article· en· W1987698311 on OpenAlex
Jason Riordon, Michael Nash, Wenyang Jing, Michel Godin

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

VenueBiomicrofluidics · 2014
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsCarleton UniversityUniversity of Ottawa
Fundersnot available
KeywordsMicrofluidicsTrap (plumbing)Volume (thermodynamics)Lab-on-a-chipCoulter counterNanotechnologyComputer scienceMaterials scienceChannel (broadcasting)EngineeringTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

We demonstrate a microfluidic device capable of tracking the volume of individual cells by integrating an on-chip volume sensor with pressure-activated cell trapping capabilities. The device creates a dynamic trap by operating in feedback; a cell is periodically redirected back and forth through a microfluidic volume sensor (Coulter principle). Sieve valves are positioned on both ends of the sensing channel, creating a physical barrier which enables media to be quickly exchanged while keeping a cell firmly in place. The volume of individual Saccharomyces cerevisiae cells was tracked over entire growth cycles, and the ability to quickly exchange media was demonstrated.

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 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 score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.030
GPT teacher head0.211
Teacher spread0.181 · 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