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Record W2080084135 · doi:10.1021/ja065855b

A Complete Microfluidic Screening Platform for Rational Protein Crystallization

2006· article· en· W2080084135 on OpenAlexaff
Billy T. C. Lau, Chris A. Baitz, Xiao Peng Dong, Carl L. Hansen

Bibliographic record

VenueJournal of the American Chemical Society · 2006
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institutes of Health
KeywordsCrystallizationMicrofluidicsChemistryEmulsionVolume (thermodynamics)Mixing (physics)SolubilityProtein crystallizationPhase (matter)NanotechnologyChemical engineeringChromatographyThermodynamicsOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

We describe a complete microfluidic screening platform for protein crystallization that integrates fully programmable on-chip combinatorial mixing with dense assay storage using two-phase flows. This device supports rational crystallization strategies based on systematic solubility phase space mapping followed by nanoliter volume crystallization screening. Sequential formulation of arbitrary chemical mixtures and injection of nanoliter volume droplets into an immiscible carrier fluid creates a water/oil emulsion with independent control over droplet chemistry, size, frequency, and spacing. Long-term incubation of droplets with controlled dehydration is used to induce crystallization.

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 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: none
Teacher disagreement score0.615
Threshold uncertainty score0.339

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 head0.015
GPT teacher head0.237
Teacher spread0.222 · 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 teacher head, 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

Citations109
Published2006
Admission routes1
Has abstractyes

Explore more

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