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Record W3159822725 · doi:10.1063/5.0039366

Transforming a well into a chip: A modular 3D-printed microfluidic chip

2021· article· en· W3159822725 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAPL Bioengineering · 2021
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsnot available
FundersAzrieli FoundationIsrael Science FoundationH2020 European Research CouncilTeva Pharmaceutical Industries
KeywordsModular designMicrofluidicsChipOrgan-on-a-chipLab-on-a-chipComputer scienceEmbedded systemMicrofluidic chipNanotechnologyComputer hardwareMaterials scienceTelecommunications

Abstract

fetched live from OpenAlex

-like conditions, i.e., in the presence of flow. Yet, the costs and know-how required for the fabrication and implementation of these platforms restrict their accessibility. This study introduces and demonstrates a novel Insert-Chip: a microfluidic device that provides the functionality of an Organ-on-a-Chip platform, namely, the capacity to co-culture cells, expose them to flow, and observe their interactions-yet can easily be integrated into standard culture systems (e.g., well plates or multi-electrode arrays). The device is produced using stereolithograpy 3D printing and is user-friendly and reusable. Moreover, its design features overcome some of the measurement and imaging challenges characterizing standard Organ-on-a-Chip platforms. We have co-cultured endothelial and epithelial cells under flow conditions to demonstrate the functionality of the device. Overall, this novel microfluidic device is a promising platform for the investigation of biological functions, cell-cell interactions, and response to therapeutics.

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 categoriesMeta-epidemiology (narrow)
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 score0.195
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.238
Teacher spread0.227 · 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