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Corrosion Behavior of Die-Cast and Thixocast AXJ530 Magnesium Alloy in Chloride Medium

2006· article· en· W1989700764 on OpenAlexaff
S. Amira, M. T. Shehata, D. Dubé, R. Tremblay, Edward Ghali

Bibliographic record

VenueAdvanced materials research · 2006
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCorrosionMaterials scienceMicrostructureMetallurgyMagnesiumAlloyMagnesium alloyImmersion (mathematics)Electrochemical noiseChloridePolarization (electrochemistry)ElectrochemistryChemistryElectrode

Abstract

fetched live from OpenAlex

The corrosion behavior of AXJ530 magnesium alloy in 3.5% NaCl solution at 25°C and pH 7.25 has been studied. Die-cast and thixocast specimens were tested using constant immersion technique, potentiodynamic polarization measurements and electrochemical noise analysis. The microstructure of cast specimens and their surface aspect after corrosion tests were analysed and compared. The results show that thixocast specimens have the best corrosion resistance. Their superior corrosion resistance can be attributed mainly to the presence of large pre-existing α-Mg grains.

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 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 score0.015
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.036
GPT teacher head0.326
Teacher spread0.290 · 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

Citations3
Published2006
Admission routes1
Has abstractyes

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