MétaCan
Menu
Back to cohort
Record W2126832734 · doi:10.1002/pat.980

Preparation and mechanical properties of poly(chitosan‐<i>g</i>‐<scp>DL</scp>‐lactic acid) fibrous mesh scaffolds

2007· article· en· W2126832734 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePolymers for Advanced Technologies · 2007
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsMaterials scienceUltimate tensile strengthChitosanSpinningLactic acidComposite materialCompressive strengthModulusScaffoldElastic modulusYoung's modulusChemical engineeringBiomedical engineering

Abstract

fetched live from OpenAlex

Abstract DL ‐lactic acid was grafted onto chitosan to produce poly(chitosan‐ g ‐ DL ‐lactic acid)(PCLA) without using a catalyst. These PCLAs were then spun into filaments and further fabricated into fibrous mesh scaffolds using an improved wet‐spinning technique. The diameter of filaments in different scaffolds could vary from a few micrometers to several tens of micrometers. The scaffolds exhibited various pore sizes ranging from about 20 µm to more than 200 µm and different porosities up to 80%. The several main processing conditions were optimized for obtaining the desired scaffolds with well‐controlled structures. The tensile and compressive mechanical properties of the mesh scaffolds in both dry and hydrated states were mainly examined. Significantly improved tensile strength and modulus, enhanced compressive modulus, and stress as well as the dimensional stability for these mesh scaffolds in their hydrated state were observed. Copyright © 2007 John Wiley &amp; Sons, Ltd.

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.

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)0.000
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 score0.187
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.252
Teacher spread0.233 · 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