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Record W4283162413 · doi:10.26434/chemrxiv-2022-1ffmn

Fabrication and assembly of thermoplastic microfluidics; a review

2022· review· en· W4283162413 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemRxiv · 2022
Typereview
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsMcMaster University
KeywordsMicrofluidicsNanotechnologyCommercializationMicrochannelFabricationAdaptabilityMaterials scienceEngineeringBiochemical engineering

Abstract

fetched live from OpenAlex

Various fields within biomedical engineering have been afforded rapid scientific advancement through the incorporation of microfluidics. As literature surrounding biological systems become more comprehensive and many microfluidic platforms show potential for commercialization, the development of representative fluidic systems has become more intricate. This has brought increased scrutiny towards the material properties of microfluidic substrates. Thermoplastics have been highlighted as a promising material, given their material adaptability and commercial compatibility. This review provides a comprehensive discussion surrounding recent developments pertaining to thermoplastic microfluidic device fabrication. Existing and emerging approaches related to both microchannel fabrication and device assembly are highlighted, with consideration towards how specific approaches induce physical and/or chemical properties that are optimally suited for relevant real-world applications.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.837
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.023
GPT teacher head0.256
Teacher spread0.233 · 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