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Record W3127814007 · doi:10.1016/j.jpha.2021.02.001

Printability–A key issue in extrusion-based bioprinting

2021· review· en· W3127814007 on OpenAlexafffund
Saman Naghieh, Daniel Chen

Bibliographic record

VenueJournal of Pharmaceutical Analysis · 2021
Typereview
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsExtrusion3D bioprintingScaffoldNanotechnology3D printingProcess (computing)Tissue engineeringComputer scienceMaterials scienceBiomedical engineeringEngineeringComposite material

Abstract

fetched live from OpenAlex

Three-dimensional (3D) extrusion-based bioprinting is widely used in tissue engineering and regenerative medicine to create cell-incorporated constructs or scaffolds based on the extrusion technique. One critical issue in 3D extrusion-based bioprinting is printability or the capability to form and maintain reproducible 3D scaffolds from bioink (a mixture of biomaterials and cells). Research shows that printability can be affected by many factors or parameters, including those associated with the bioink, printing process, and scaffold design, but these are far from certain. This review highlights recent developments in the printability assessment of extrusion-based bioprinting with a focus on the definition of printability, printability measurements and characterization, and printability-affecting factors. Key issues and challenges related to printability are also identified and discussed, along with approaches or strategies for improving printability in extrusion-based bioprinting.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.080
GPT teacher head0.440
Teacher spread0.360 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations254
Published2021
Admission routes2
Has abstractyes

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Same venueJournal of Pharmaceutical AnalysisSame topic3D Printing in Biomedical ResearchFrench-language works237,207