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Record W2109507330 · doi:10.1109/ias.1997.626283

Electrostatic lubrication of moulds

2002· article· en· W2109507330 on OpenAlexaff
J. D. Brown, G.S.P. Castle, François Chagnon, I.I. Inculet

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInjection Molding Process and Properties
Canadian institutionsCégep de Sorel-TracyWestern University
Fundersnot available
KeywordsLubricationMaterials scienceLubricantPowder metallurgyPowder coatingMetallurgyComposite materialCoatingInjection mouldingMicrostructure

Abstract

fetched live from OpenAlex

A prototype dry electrostatic powder lubrication system for lubrication of powder metallurgy moulds was designed. The system uses contact electrification to charge the powder and an electric field to aid in uniform coating of the internal surfaces of the mould. The system was mounted on a 200 ton press and the sequence used in lubrication of the mould was compatible with the press sequence in which the parts are produced. Parts which were made using the prototype system and reduced lubricant powder concentration in the metal powder formulation had increased green density and strength while still maintaining equivalent surface finish and mould lubrication for successful moulding of parts.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.160
Teacher spread0.148 · 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 source (direct Gemma or distilled Codex), 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
Published2002
Admission routes1
Has abstractyes

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