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Record W1988603287 · doi:10.1039/c1lc90069b

Education: A modular approach to microfluidics in the teaching laboratory

2011· article· en· W1988603287 on OpenAlexaff
Yolanda Fintschenko

Bibliographic record

VenueLab on a Chip · 2011
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsGlycemic Index Laboratories
FundersDirectorate for STEM EducationUniversity of California, Santa BarbaraWest Virginia University
KeywordsMicrofluidicsModular designEngineering ethicsEngineeringGraduate studentsMathematics educationComputer scienceBiological engineeringEngineering managementNanotechnologyPedagogyPsychologyBioinformaticsBiologyMaterials science

Abstract

fetched live from OpenAlex

This article seeks to educate the reader about the role played by the microfluidics teaching lab in the education of science, technology, engineering and mathematics for students of all ages. The discussion is intended to serve as a general guide to educators about the lab philosophy, goals, lab experiments and required equipment and reagents necessary for a successful microfluidics teaching laboratory. We hope that this article will stimulate other groups and companies to describe what they are doing to encourage education in this sector. At LabSmith we have developed a modular approach for teaching and demonstrating microfluidics that allows the end user to tailor the laboratory to course goals without an impact on the package of experimental equipment required and available to them. Thus, it is possible to educate students either in the art of microfluidics or use microfluidics to educate students about fundamental physical, chemical, or biological principles. The laboratory experiments discussed here are for students with educational experience at high school, undergraduate, graduate, and post-graduate levels.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.390

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 head0.013
GPT teacher head0.208
Teacher spread0.195 · 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 designNot applicable
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

Citations40
Published2011
Admission routes1
Has abstractyes

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