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Record W4280506356 · doi:10.3389/fbioe.2022.849831

Hydrogels for Tissue Engineering: Addressing Key Design Needs Toward Clinical Translation

2022· review· en· W4280506356 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

VenueFrontiers in Bioengineering and Biotechnology · 2022
Typereview
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of VictoriaMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsKey (lock)Translation (biology)Self-healing hydrogelsTissue engineeringComputer scienceHuman–computer interactionBiomedical engineeringEngineeringChemistryChemical engineeringComputer securityBiochemistry

Abstract

fetched live from OpenAlex

tissue engineering. We suggest that combining such integrated fabrication approaches with the lessons learned from previously successful translational experiences with other hydrogels represents a promising strategy to accelerate the implementation of hydrogels for tissue engineering in the clinic.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.002
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 head0.157
GPT teacher head0.364
Teacher spread0.207 · 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