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Record W3193589377 · doi:10.31399/asm.cp.itsc2000p0887

Powder Spheroidization Using Induction Plasma Technology

2000· article· en· W3193589377 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

VenueThermal spray · 2000
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced ceramic materials synthesis
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMaterials sciencePlasmaEvaporationRange (aeronautics)OxideCubic zirconiaMetallurgyMaximum power principleNuclear engineeringPower (physics)Composite materialThermodynamicsCeramic

Abstract

fetched live from OpenAlex

Abstract An experimental study of the spheroidization efficiency of induction plasma processes was completed. The main objective being to obtain models which could be subsequently used for the prediction of the spheroidization efficiency for various powders and plasma operating conditions. Silica, alumina, chromium oxide and zirconia powders were treated during the experimentation. For the plasma treatment of the powders the installation used had a maximum available power of 50 kW with an operating frequency of 3 MHz. Operating conditions were varied such to minimize side reactions and the evaporation of powders. The resulting powders did show the presence of cavities and a slight change in the mean diameters. The maximum energy efficiency based semi-empirical model did predict the spheroidization efficiency of the particles beyond a defined critical point known as the maximum energy efficiency point. For the model, the maximum energy efficiency is distinct for the individual powders but remain within a defined range which is reflected in the small variations in the Z constant.

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 categoriesInsufficient 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 score0.024
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)0.0240.001

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 head0.014
GPT teacher head0.242
Teacher spread0.228 · 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