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Direct super-resolution imaging of the disordered and crystalline nanostructure of bacterial cellulose fibrils

2025· preprint· W4416769937 on OpenAlexafffund
Mouhanad Babi, Anthony Palermo, Tíffany Abitbol, Ayodele Fatona, Victoria Jarvis, Akanksha Nayak, Emily D. Cranston, Jose Moran‐Mirabal

Bibliographic record

VenueChemRxiv · 2025
Typepreprint
Language
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British ColumbiaMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsBacterial celluloseCelluloseNanostructureFibrilAmorphous solidNanocrystalDegradation (telecommunications)Microscopy

Abstract

fetched live from OpenAlex

Cellulose is composed of tightly packed glucan chains that give it superior strength but render it recalcitrant to breakdown. The presence of dislocations susceptible to degradation within cellulose fibrils has been postulated for decades, but they have never been directly visualized. We have developed a super-resolution fluorescence microscopy approach to visualize alternating crystalline and disordered regions within bacterial cellulose fibrils. The measured size of crystalline regions ranges from 40 – 400 nm and matches the length distribution of cellulose nanocrystals produced through acid hydrolysis, while disordered regions are 20 – 120 nm long, heterogeneous and do not form large amorphous pockets. These results lend strong support for the fringed-micellar model of cellulose fibrils and provide fundamental insight into the role of cellulose nanostructure in its breakdown by chemical and enzymatic means.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.266
Teacher spread0.253 · 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 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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