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Record W4210817127 · doi:10.35493/medu.38.8

Spider Silk in Tissue Engineering

2021· article· en· W4210817127 on OpenAlexvenueno aff
Hannah Silverman, Matthew Lynn

Bibliographic record

VenueThe Meducator · 2021
Typearticle
Languageen
FieldMaterials Science
TopicSilk-based biomaterials and applications
Canadian institutionsnot available
Fundersnot available
KeywordsSILKSpider silkSpiderBiologyPolymer scienceZoologyComputer scienceMaterials science

Abstract

Spider Silk in Tissue EngineeringThe biomedical applications of spider silk can be traced back to ancient Roman times, where silk fibre meshes were used to treat skin lesions.1 Today, spider silk is commonly used as a suturing material in eye, intraoral, and lip surgeries due to its strength and extensibility.2However, new applications for spider silk have been identified in the field of tissue engineering, with potential uses ranging from meshes and coatings to scaffolding for tissue regeneration.3These applications take advantage of spider silk's biocompatibility and high tensile strength to promote cardiac tissue regeneration, peripheral axon myelination, bone regeneration, and cartilage growth.3In this article, the latest large-scale production methods and several promising applications of spider silk are reviewed.

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: venue_new · design weight: 2684.25 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: other
about Canada: no
confidence: high

Short review of spider silk applications in tissue engineering; a biomaterials topic.

GPT-5.6 (high)OUT
genre: conceptual
about Canada: no
confidence: high

It reviews biomedical applications of spider silk rather than research practice.

Grok 4.5OUT
genre: other
about Canada: no
confidence: high

Biomedical review of spider silk for tissue engineering applications, not research as object.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.002
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.015
GPT teacher head0.269
Teacher spread0.254 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueThe MeducatorSame topicSilk-based biomaterials and applicationsFrench-language works237,207