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Record W3097153958 · doi:10.1042/bst20200310

From protocells to prototissues: a materials chemistry approach

2020· review· en· W3097153958 on OpenAlexfundno aff
Pierangelo Gobbo

Bibliographic record

VenueBiochemical Society Transactions · 2020
Typereview
Languageen
FieldEngineering
TopicModular Robots and Swarm Intelligence
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilCanadian Institutes of Health ResearchUniversity of Bristol
KeywordsProtocellFunction (biology)Computer scienceSynthetic biologyNanotechnologyField (mathematics)Human–computer interactionBiochemical engineeringData scienceArtificial intelligenceEngineeringChemistryBiologyComputational biologyMaterials scienceMathematics

Abstract

fetched live from OpenAlex

Prototissues comprise free-standing 3D networks of interconnected protocell consortia that communicate and display synergistic functions. Significantly, they can be constructed from functional molecules and materials, providing unprecedented opportunities to design tissue-like architectures that can do more than simply mimic living tissues. They could function under extreme conditions and exhibit a wide range of mechanical properties and bio-inspired metabolic functions. In this perspective, I will start by describing recent advancements in the design and synthetic construction of prototissues. I will then discuss the next challenges and the future impact of this emerging research field, which is destined to find applications in the most diverse areas of science and technology, from biomedical science to environmental science, and soft robotics.

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)0.000
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.002

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 head0.034
GPT teacher head0.276
Teacher spread0.242 · 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

Citations36
Published2020
Admission routes1
Has abstractyes

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