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Record W4392241052 · doi:10.3390/jof10030183

From Nature to Design: Tailoring Pure Mycelial Materials for the Needs of Tomorrow

2024· review· en· W4392241052 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

VenueJournal of Fungi · 2024
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and Biological Electrophysiology Studies
Canadian institutionsUniversity of VictoriaMcMaster University
FundersMcMaster University
KeywordsMyceliumNanotechnologyBiochemical engineeringProcess (computing)Fungal DiversityArchitectural engineeringComputer scienceEngineeringMaterials scienceBotanyBiology

Abstract

fetched live from OpenAlex

Modern efforts to influence materials science with principles of biology have allowed fungal mycelial materials to take a foothold and develop novel solutions for the circular bioeconomy of tomorrow. However, recent studies have shown that the value of tomorrow's green materials is not determined simply by their environmental viability, but rather by their ability to make the polluting materials of today obsolete. With an inherently strong structure of chitin and β-glucan, the ever-adaptable mycelia of fungi can compete at the highest levels with a litany of materials from leather to polyurethane foam to paper to wood. There are significant efforts to optimize pure mycelial materials (PMMs) through the entire process of species and strain selection, mycelial growth, and fabrication. Indeed, the promising investigations of novel species demonstrate how the diversity of fungi can be leveraged to create uniquely specialized materials. This review aims to highlight PMMs' current trajectory, evaluate the successes in technology, and explore how these new materials can help shape a better tomorrow.

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 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 score0.956
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.068
GPT teacher head0.301
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