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Record W2980158956 · doi:10.1039/c9lc00779b

A single-phase flow microfluidic cell sorter for multiparameter screening to assist the directed evolution of Ca<sup>2+</sup> sensors

2019· article· en· W2980158956 on OpenAlexafffund
Y Zhao, Wei Zhang, Yongxin Zhao, Robert E. Campbell, D. Jed Harrison

Bibliographic record

VenueLab on a Chip · 2019
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsAlberta Hospital EdmontonUniversity of Alberta
FundersNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health ResearchFoundation for the National Institutes of HealthAlberta Innovates - Technology FuturesNatural Sciences and Engineering Research Council of CanadaFondation Brain Canada
KeywordsMicrofluidicsPhase (matter)Continuous flowNanotechnologyFluorescenceBiophysicsChemistryMaterials sciencePhysicsBiologyOpticsMechanics

Abstract

fetched live from OpenAlex

We introduce a single-phase flow microfluidic cell sorter with a two-point detection system capable of two-parameter screening to assist with directed evolution of a fluorescent protein based Ca 2+ sensor expressed in bacterial cells.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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

Citations14
Published2019
Admission routes2
Has abstractyes

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