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Record W2007773113 · doi:10.1039/c3lc00020f

An electrochemical Lab-on-a-CD system for parallel whole blood analysis

2013· article· en· W2007773113 on OpenAlexafffund
Tingjie Li, Yaxi Fan, Cheng Yang, Jun Yang

Bibliographic record

VenueLab on a Chip · 2013
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsWhole bloodBioanalysisComputer scienceProcess engineeringLab-on-a-chipBiochemical engineeringNanotechnologyChemistryMicrofluidicsEngineeringChromatographyMaterials scienceBiologyImmunology

Abstract

fetched live from OpenAlex

Lab-on-a-CD, as a main branch of Lab-on-a-chip technology, has led to several very successful commercial products. Most of these existing Lab-on-a-CD systems present complex system designs and thus are relatively expensive. In this work, we have developed a simple but robust Lab-on-a-CD system for parallel whole blood analyses. This Lab-on-a-CD system incorporates electrochemical bioanalysis and a simple blood sample separation mechanism into the centrifugal platform, and thus reduces the system's complexity. To demonstrate the applicability, the system was applied to perform basic metabolic panel tests, for example, the concentrations of glucose, lactate and uric acids of whole blood samples. Using only 16 μL of whole blood, within a few minutes, the Lab-on-a-CD system could produce results that agreed in general with the data by a conventional system. Therefore, this proof-of-concept Lab-on-a-CD system has demonstrated the potential to become a robust and simple-to-use device for parallel blood analyses.

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: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.687

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 head0.005
GPT teacher head0.202
Teacher spread0.196 · 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

Citations41
Published2013
Admission routes2
Has abstractyes

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