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Record W4316662187 · doi:10.18280/rcma.320602

An In-Depth Study of Magnesium Composite in Various Corrosive Media: Insight in Orthopedic Implant

2022· article· fr· W4316662187 on OpenAlexvenueno aff
Adedotun Adetunla, Bernard Adaramola, Omolayo M. Ikumapayi, Ebenezer Olubunmi Ige, Sunday A. Afolalu

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2022
Typearticle
Languagefr
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMagnesiumOrthopedic surgeryComposite numberDentistryImplantMaterials scienceMedicineOrthodonticsMetallurgyComposite materialSurgery

Abstract

fetched live from OpenAlex

The majority of the properties required for orthopedic implant operation are demonstrated by magnesium and its alloys, however, the metal degrades rapidly in the body's environment.Therefore, a magnesium-based metal matrix composite capable of safely and gradually degrading in the body within the required healing time is required, thereby eliminating the need for a second surgery.The degradability of this newly formed alloy was done via corrosion test of this alloy in various corrosive media namely, H20, NaCl, Urine, Blood, and Plasma.Three samples A (50% reinforcement), B (25% reinforcement), and C (No reinforcement) of grade AZ31B Magnesium alloy and Calcium Carbonate powder reinforcement were developed via stir-casting technique.The impact strength of this alloy was carried out by using Charpy Impact Tester, while the microstructural characterization was determined by Scanning Electron Microscope (SEM).

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 score0.002

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 integrity0.0000.000
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 head0.051
GPT teacher head0.287
Teacher spread0.236 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueRevue des composites et des matériaux avancésSame topicMagnesium Alloys: Properties and ApplicationsFrench-language works237,207