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Record W2597062408 · doi:10.1166/jnn.2017.14292

A Note on the Role of Spatial Scale in Imaging Collagen Hydrogels

2017· article· en· W2597062408 on OpenAlexaff
Amir K. Miri

Bibliographic record

VenueJournal of Nanoscience and Nanotechnology · 2017
Typearticle
Languageen
FieldMaterials Science
TopicCollagen: Extraction and Characterization
Canadian institutionsMcGill University
Fundersnot available
KeywordsSelf-healing hydrogelsCollagen fibrilMaterials scienceFibrilCharacterization (materials science)Biomedical engineeringOrientation (vector space)Tissue engineeringBiophysicsNanotechnologyPolymer chemistryMedicineBiologyGeometry

Abstract

fetched live from OpenAlex

Fibrillar collagen hydrogels have been used widely as bioactive scaffolds for multiple applications in biomedical and tissue engineering. The physical functions of collagen fibrils are regulated by their underlying microstructure—represented by fibrillar density and orientation. The extent to which characterization techniques are used for imaging collagen fibrillar networks has significantly reduced the usefulness of published data for biomedical engineers. This short communication explains the level of uncertainty surrounding fibrillar orientation measurements. It is discussed how a correlation between the orientation of collagen fibrils and normal distribution function can provide a robust baseline for comparative research in imaging collagen.

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)0.004
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.250
Teacher spread0.242 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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