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Record W1983289359 · doi:10.1088/1009-0630/5/4/009

Radio Frequency Induction Plasma Spraying of Molybdenum

2003· article· en· W1983289359 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

VenuePlasma Science and Technology · 2003
Typearticle
Languageen
FieldEngineering
TopicAdvanced materials and composites
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMolybdenumPlasmaRadio frequencyMaterials sciencePhysicsAtomic physicsChemistryMetallurgyNuclear physicsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Radio frequency (RF) induction plasma was used to make free-standing deposition of molybdenum (Mo). The phenomena of particle melting, flattening, and stacking were investigated. The effect of process parameters such as plasma power, chamber pressure, and spray distance on the phenomena mentioned above was studied. Scanning electron microscopy (SEM) was used to analyze the plasma-processed powder, splats formed, and deposits obtained. Experimental results show that less Mo particles are spheroidized when compared to the number of spheroidized tungsten (W) particles at the same powder feed rate under the same plasma spray condition. Molten Mo particles can be sufficiently flattened on substrate. The influence of the process parameters on the flattening behavior is not significant. Mo deposit is not as dense as W deposit, due to the splash and low impact of molten Mo particles. Oxidation of the Mo powder with a large particle size is not evident under the low pressure plasma spray.

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 score0.033
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.196
Teacher spread0.189 · 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