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Record W7132869160

A Roll-to-Roll Mechanism for the Scalable Fabrication of Aligned Collagen Scaffolds for Load-Bearing Tissues

2025· dissertation· W7132869160 on OpenAlexafffund
Samuel Lasinski

Bibliographic record

VenueTSpace · 2025
Typedissertation
Language
FieldMaterials Science
TopicCollagen: Extraction and Characterization
Canadian institutionsToronto Rehabilitation Institute
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFabricationExtracellular matrixMatrix (chemical analysis)Tissue engineeringMechanism (biology)Structural integrityNanoscopic scaleScale (ratio)
DOInot available

Abstract

fetched live from OpenAlex

Collagen is the primary structural component of the extracellular matrix and is critical to the mechanical integrity of load-bearing tissues such as tendon, bone, and blood vessels. In these tissues, collagen is often highly aligned, with fibers oriented in the direction of physiological loading. The Guenther lab previously developed a wet-spinning approach to generate ultrathin collagen sheets with physiologically relevant alignment; however, this approach is limited in the amount of sheet it can produce, posing a barrier to the fabrication of human scale constructs. In this thesis, we present a roll-to-roll manufacturing approach for the scalable production of aligned collagen sheets, achieving an order-of-magnitude increase in length and enabling the possibility of fabricating human scale tissues. To our knowledge, this is the first demonstration of roll-to-roll processing for planar, wet-spun biomaterials manufacturing. Additionally, we demonstrate the rolling of these sheets with deposited collagen hydrogel layers into heterogenous tubular structures.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.310
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.342
Teacher spread0.314 · 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
Published2025
Admission routes2
Has abstractyes

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