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Record W2965112455 · doi:10.3390/mi10080501

3D Printing Breast Tissue Models: A Review of Past Work and Directions for Future Work

2019· review· en· W2965112455 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

VenueMicromachines · 2019
Typereview
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsInnovate BC
KeywordsTissue engineeringBreast cancer3D bioprintingWork (physics)Computer scienceBiomedical engineeringBiochemical engineeringEngineeringMedicineCancerMechanical engineering

Abstract

fetched live from OpenAlex

Breast cancer often results in the removal of the breast, creating a need for replacement tissue. Tissue engineering offers the promise of generating such replacements by combining cells with biomaterial scaffolds and serves as an attractive potential alternative to current surgical repair methods. Such engineered tissues can also serve as important tools for drug screening and provide in vitro models for analysis. 3D bioprinting serves as an exciting technology with significant implications and applications in the field of tissue engineering. Here we review the work that has been undertaken in hopes of generating the recognized in-demand replacement breast tissue using different types of bioprinting. We then offer suggestions for future work needed to advance this field for both in vitro and in vivo 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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.038
GPT teacher head0.333
Teacher spread0.295 · 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