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1006 Production of Sintered Bearing by Unification Powder Forming from Different Metals Powder

2012· article· en· W2690797504 on OpenAlexaff
Toshihiko MOURI, Yousuke SUGAI, Makoto SHIRANAMI, Fuminori SATOJI, Mitsuo ARASHIDA, Eiji Yuasa

Bibliographic record

VenueKikai Zairyou, Zairyou Kakou Gijutsu Kouenkai kouen rombunshuu/Kikai Zairyo, Zairyo Kako Gijutsu Koenkai koen ronbunshu · 2012
Typearticle
Languageen
FieldEngineering
TopicPowder Metallurgy Techniques and Materials
Canadian institutionsFédération des Comités de Parents du Québec
Fundersnot available
KeywordsMaterials scienceSinteringMetallurgyBearing (navigation)Layer (electronics)Electron microprobeComposite numberComposite materialDiffusion

Abstract

fetched live from OpenAlex

For the production of the composite journal bearings (CJB) with high strength and high wear resistance, two different mixed powders were compacted in the shape of a double-layers cylinder. A mixed powder of Fe-Cu was used for an outer layer as back-up material. In inner layer, the mixed powder of Fe-Ni-Mo-Cu was used for wear resistance. The compacted cylindrical bearing was sintered at various temperatures. A distribution of elemental composition in the laminating interface neighborhood was analyzed by the EPMA. As a result, the CJB was confirmed that joining between inner layer and outer layer materials is made by the diffusion mechanism and it became to higher hardness with increasing of sintering temperature. The hardness of the CJB increases with increasing of sintering temperature, and after the sizing process, the CJB became higher circularity than journal bearing made by conventional P/M process.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
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 score0.073
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.006
Open science0.0040.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.229
Teacher spread0.214 · 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; both teacher heads agree on what is shown here.

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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