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Record W2789607115 · doi:10.1039/c8ra00404h

Long-term <i>in vitro</i> degradation behaviour of Fe and Fe/Mg<sub>2</sub>Si composites for biodegradable implant applications

2018· article· en· W2789607115 on OpenAlexafffund
Małgorzata Sikora-Jasinska, Pascale Chevallier, Stéphane Turgeon, Carlo Paternoster, Ehsan Mostaed, Maurizio Vedani, Diego Mantovani

Bibliographic record

VenueRSC Advances · 2018
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaMinistero dell’Istruzione, dell’Università e della RicercaUniversité Laval
KeywordsDegradation (telecommunications)Materials scienceTerm (time)Composite materialImplantComputer scienceMedicineTelecommunicationsPhysicsSurgery

Abstract

fetched live from OpenAlex

Si composites showed higher degradation rates than those of pure Fe at all stages of immersion. Degradation rates at distinct exposure intervals strongly depended on the composition and stability of formed oxide, hydroxide, carbonate and phosphate protective films on the degraded surfaces. The release of Fe ions into the solution at later stages of the experiment was limited due to the barrier effect of the insoluble deposit. This fundamental study provided a basis for the processes of protective film formation in modified Hanks' solution, which enables a detailed identification of its characteristic features.

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 score0.011
Threshold uncertainty score0.471

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 head0.014
GPT teacher head0.258
Teacher spread0.243 · 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

Citations26
Published2018
Admission routes2
Has abstractyes

Explore more

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