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Record W2092696955 · doi:10.1179/174329409x439050

Nanostructured composite coatings for oil sand's applications

2009· article· en· W2092696955 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSurface Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvanced materials and composites
Canadian institutionsHyperion Technologies (Canada)University of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceThermal sprayingHardfacingCoatingAbrasiveMetallurgyComposite numberSubstrate (aquarium)WeldingComposite material

Abstract

fetched live from OpenAlex

Machinery used in mining and mineral processing industry suffers from severe degradation through abrasive wear. The current techniques used to extend the wear life of components exposed to these environments include the heat treatment of steels and the hardfacing of surfaces using fusion welding techniques. However, thermal spraying techniques such as the use of high velocity oxy-fuel (HVOF) composite coatings based on WC–Co system offer better wear resistance and greater flexibility in application. The ability to deposit microstructured coatings by the HVOF process is well established, but the ability to deposit nanostructured coatings is relatively new and posses a challenge. This paper reviews the application of the HVOF coating technique, and compares the wear resistant behaviour of a C–Mn steel substrate coated using micro- and nanostructured WC–Co based coatings.

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)0.000
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 score0.396
Threshold uncertainty score0.721

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 head0.003
GPT teacher head0.194
Teacher spread0.190 · 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