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Microbiologically induced intergranular corrosion of 316L stainless steel dental material in saliva

2023· article· en· W4389621759 on OpenAlexafffund
Ubong Eduok

Bibliographic record

VenueMaterials Chemistry and Physics · 2023
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsCorrosionDentistryBiocompatibilityMaterials scienceMetallurgyPeri-implantitisIntergranular corrosionMetalPorphyromonas gingivalisOral hygienePeriodontitisAlloySalivaMedicineImplantSurgeryInternal medicine

Abstract

fetched live from OpenAlex

The release of certain metallic constituents within some dental implants could contribute to peri-implantitis and mucositis . While the release rate into surrounding bones and tissues may be dependent on the biocompatibility of dental materials and their designs, the patient's oral hygiene and even the prevalence of certain resident oral bacteria may also affect the service lives of these dental implants by altering their gross corrosion rates . In this study, the levels of Fe, Cr, and Ni released during microbiologically induced intergranular corrosion of medical grade 316L stainless-steel dental material are measured across defined culture durations. Porphyromonas gingivalis , a prominent component of the oral microbiome known to associate with periodontitis and peri-implantitis, is the test bacterium in this study. From the evidence obtained from electrochemical and surface investigations in artificial salivary culture media, dental substates corroded significantly upon maturation of bacterial growth. Corrosion was accompanied by higher levels of metal ion release at extended culture duration. About 1.5 and 9.5 μg/cm 2 of Ni and Cr were leached from the metal alloy after a 30-day exposure to the bacterial culture relative to the control; Fe was released 30 times more in the former. This study highlights how oral metal contact influences the corrosion of metallic dental implants (e.g., stainless-steel crowns) in patients infected by certain resident oral bacterium.

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)0.000
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 score0.010
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.255
Teacher spread0.240 · 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

Citations16
Published2023
Admission routes2
Has abstractyes

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