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Characterization of Phosphate Glass Reinforced Gelatin Blend Bioactive Composite Films

2014· article· en· W2032652572 on OpenAlexvenueno aff
Kamol Dey, Poonam Alamgir, Shahnaz Parvin, Gulshana Mohol, Wafa Tonny, Mubarak A. Khan, Ruhul A. Khan

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2014
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsnot available
FundersUniversidad de Antioquia
KeywordsMaterials scienceComposite numberGelatinThermogravimetric analysisMethacrylateComposite materialCastingPolymerMonomerChemical engineeringOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

Bioactive composite films were prepared using bioresorbable phosphate glass powder and biodegradable polymer gelatin (G) through solution casting process. Biocompatible monomer, 2-hydroxyethyl methacrylate (HEMA) was used as the cross-linking agent and bioresorbable phosphate glass (PG) powder was used as reinforcement filler. The composite films were obtained at various ratios of G, PG and HEMA. The PG modified gelatin composite (PG/G) film was fabricated at a weight ratio of 12:88 while HEMA modified gelatin composite (HEMA/G) film at 50:50 ratio. On the other hand, hybrid gelatin composite film, containing both PG and HEMA, was obtained using a G/PG/HEMA ratio of 44:12:44. Incorporation of PG improved the mechanical properties of the composite films. Morphological property of the composite films was investigated by stereo microscope and it revealed that the composite films were porous in nature. The thermal behaviour of the films was studied using thermogravimetric analysis. Water uptake of the films was also performed.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.054
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.015
GPT teacher head0.285
Teacher spread0.271 · 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.

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
Published2014
Admission routes1
Has abstractyes

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