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Record W4391888670 · doi:10.1016/j.jmbbm.2024.106467

An interferometric-based tensile tester to resolve damage events within reconstituted multi-filaments collagen bundles

2024· article· en· W4391888670 on OpenAlexafffund
Hessameddin Yaghoobi, Chloe Tremblais, Alex Gareau, Matthieu Cointe, Alexey B. Tikhomirov, Laurent Kreplak, D. Labrie

Bibliographic record

VenueJournal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials · 2024
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceUltimate tensile strengthInterferometryFiberSlippageCantileverTensile testingDisplacement (psychology)MicroscopyComposite materialBiomedical engineeringOpticsEngineering

Abstract

fetched live from OpenAlex

Understanding how mechanical damage propagates in load-bearing tissues such as skin, tendons and ligaments, is key to developing regenerative medicine solutions for when these tissues fail. For collagenous tissues in particular, damage is typically assessed after mechanical testing using a broad range of microscopy techniques because standard tensile testing systems do not have the time and force sensitivity to resolve mechanical damage events. Here we introduce an interferometric detection scheme to measure the displacement of a cantilever with a resolution of 0.03% of full scale at a sampling rate of 5000 samples/s. The system is validated using collagen fibers engineered to mimic mammalian tendons. The system can detect sudden decrease in force due to slippage between collagen filaments, one to five microns in diameter, within a fiber in air. It can also detect yield events associated with local collagen unfolding or sliding within collagen fibrils within a fiber in liquid. This is opening the road to the sub-failure study of damage propagation within a broad range of hierarchical biomaterials.

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 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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.330
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materialsSame topicTendon Structure and TreatmentFrench-language works237,207