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Record W2023133238 · doi:10.1179/003258901666437

Electrical resistivity of green powder compacts

2001· article· en· W2023133238 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

VenuePowder Metallurgy · 2001
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsElectrical resistivity and conductivityMaterials scienceParticle sizeParticle (ecology)MetallurgyComposite materialParticle-size distributionElectrical resistance and conductanceChemical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

Different parameters affect the electrical resistivity of green specimens. This paper presents the effect of the particle size distribution, the compacting pressure, and the oxidation of the powder on the electrical resistivity of green specimens fabricated with different powders (Fe, Zn, Ni, and Cu). The results show that the electrical resistivity increases when the compacting pressure decreases, the particle size is reduced and the oxidation increases. It indicates that the electrical resistivity is sensitive to powder surface characteristics and particle interfaces in green compacts. Electrical resistivity may therefore be used to study particle interfaces, evaluate green powder compact characteristics, and monitor powder oxidation.

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 categoriesInsufficient payload (model declined to judge)
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 score0.035
Threshold uncertainty score0.999

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)0.0020.000

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 head0.021
GPT teacher head0.263
Teacher spread0.242 · 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