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Metallurgical parameters controlling matrix/B<sub>4</sub>C particulate interaction in aluminium–boron carbide metal matrix composites

2013· article· en· W1998514339 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Cast Metals Research · 2013
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsUniversité du Québec à Chicoutimi
FundersNational Plan for Science, Technology and Innovation
KeywordsMaterials scienceBoron carbideAlloy6063 aluminium alloyAluminiumMetallurgyScanning electron microscopeComposite materialCastingBoronMetalMetal matrix compositeCarbideField emission microscopy

Abstract

fetched live from OpenAlex

Two base matrixes of Al–15 vol.-%B4C and 6063–15 vol.-%B4C metal matrix composites (MMCs) were produced using a powder injection technique. Alloying element additions of 0·5 wt-%Ti, 0·35 wt-%Zr and 0·35 wt-%Sc were added to the base matrixes to produce various alloy compositions of Al–15 vol.-%B4C and 6063–15 vol.-%B4C MMCs. The production route of the MMCs used in the current project was the molten metal processing technique using powder injection. For the purpose of investigating the reinforcement (B4C)/matrix (Al) interaction, five alloy compositions of pure Al–15 vol.-%B4C and 6063–15 vol.-%B4C with various additions of Ti, Zr and Sc were produced. A metallic L shaped mould was used for casting the aluminium MMCs. Reinforcement/matrix interface interactions in the produced composites were investigated, using a field emission gun scanning electron microscope and energy dispersive X-ray techniques, as a function of alloying element addition.

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.

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)0.002
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 score0.186
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.041
GPT teacher head0.336
Teacher spread0.295 · 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