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Record W3132994358 · doi:10.1088/1758-5090/abe7ab

Printability in extrusion bioprinting

2021· letter· en· W3132994358 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

VenueBiofabrication · 2021
Typeletter
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaOffice of Research, Drexel University
KeywordsExtrusion3D bioprintingMaterials scienceFormabilityBiomaterialNanotechnologyTissue engineeringComposite materialBiomedical engineeringEngineering

Abstract

fetched live from OpenAlex

Extrusion bioprinting has been widely used to extrude continuous filaments of bioink (or the mixture of biomaterial and living cells), layer-by-layer, to build three-dimensional constructs for biomedical applications. In extrusion bioprinting, printability is an important parameter used to measure the difference between the designed construct and the one actually printed. This difference could be caused by the extrudability of printed bioink and/or the structural formability and stability of printed constructs. Although studies have reported in characterizing printability based on the bioink properties and printing process, the concept of printability is often confusingly and, sometimes, conflictingly used in the literature. The objective of this perspective is to define the printability for extrusion bioprinting in terms of extrudability, filament fidelity, and structural integrity, as well as to review the effect of bioink properties, bioprinting process, and construct design on the printability. Challenges related to the printability of extrusion bioprinting are also discussed, along with recommendations for improvements.

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)0.001
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.614
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0010.002
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 head0.030
GPT teacher head0.263
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