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Record W2468730293 · doi:10.31399/asm.cp.itsc2012p0190

The Effects of Abrasive Conditions on the Performance of Tungsten Carbide-Based Metal Matrix Composite Overlays

2012· article· en· W2468730293 on OpenAlexaff
G. Fisher, Tonya Wolfe

Bibliographic record

VenueThermal spray · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced materials and composites
Canadian institutionsAlberta Innovates
Fundersnot available
KeywordsOverlayMaterials scienceComposite numberAbrasiveTungsten carbideTungstenWear resistanceMetallurgyCarbideComposite materialMatrix (chemical analysis)Computer science

Abstract

fetched live from OpenAlex

Abstract Typically, standard alloys do not have the wear resistance properties necessary to combat the aggressive wear and corrosive conditions prevalent throughout the oil sands mining process. For production-critical components, it is common to apply tungsten carbide-based metal matrix composite (WC-MMC) overlays to extend equipment life and prevent unplanned outages. The performance of composite overlays is very much dependent on the wear-environment. This paper will discuss how the interactions between abrasive conditions and the mechanical and structural properties of the WC-MMCs are key in determining the resultant levels of performance. Such information can lead to a better selection of materials and subsequent extended component life.

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 score0.027
Threshold uncertainty score0.242

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 head0.004
GPT teacher head0.208
Teacher spread0.204 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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