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Record W4396498916 · doi:10.1088/1748-605x/ad45d6

Cytotoxicity of novel hybrid composite materials for making bone fracture plates

2024· article· en· W4396498916 on OpenAlexaff
Aurelia Bihari, Aaron Gee, Habiba Bougherara, Pawel Brzozowski, Abdel‐Rahman Lawendy, Emil H. Schemitsch, Radovan Zdero

Bibliographic record

VenueBiomedical Materials · 2024
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsUniversity of TorontoToronto Metropolitan UniversityVictoria Hospital
Fundersnot available
KeywordsMaterials scienceComposite numberComposite materialCytotoxicityFracture (geology)

Abstract

fetched live from OpenAlex

Bone fracture plates are usually made from steel or titanium, which are much stiffer than cortical bone. This may cause bone 'stress shielding' (i.e. bone resorption leading to plate loosening) and delayed fracture healing (i.e. fracture motion is less than needed to stimulate callus formation at the fracture). Thus, the authors previously designed, fabricated, and mechanically tested novel 'hybrid' composites made from inorganic and organic materials as potential bone fracture plates that are more flexible to reduce these negative effects. This is the first study to measure the cytotoxicity of these composites via the survival of rat cells. Cubes of carbon fiber/flax fiber/epoxy and glass fiber/flax fiber/epoxy had better cell survival vs. Kevlar fiber/flax fiber/epoxy (57% and 58% vs. 50%). Layers and powders made of carbon fiber/epoxy and glass fiber/epoxy had higher cell survival than Kevlar fiber/epoxy (96%-100% and 100% vs. 39%-90%). The presence of flax fibers usually decreased cell survival. Thus, carbon and glass fiber composites (with or without flax fibers), but not Kevlar fiber composites (with or without flax fibers), may potentially be used for bone fracture plates.

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)0.000
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 score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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