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Record W4294830511 · doi:10.31399/asm.cp.itsc2006p0133

Low Pressure Gas Dynamic Spray Forming Near-net Shape Parts

2006· article· en· W4294830511 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 · 2006
Typearticle
Languageen
FieldEngineering
TopicMaterials Engineering and Processing
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsSizingMaterials scienceComposite materialSpray formingThermalThermal sprayingMachiningSinteringProcess (computing)DurabilityMechanical engineeringMetallurgyComputer scienceMicrostructureEngineering

Abstract

fetched live from OpenAlex

Abstract Thermal spraying processes are well known in industry for providing relatively dense components. The Gas Dynamic Spray (GDS) technologies are a growing alternative, especially after the great success of certain applications such as plasma and thermal spray formed components. One of the advantages of GDS is the possibility to obtain complex thin-walled shapes of various powder materials and composites. The optional post-spraying processes such as sintering, sizing and little machining may be applied. Using the low pressure radial injection GDS method, some new thin wall components have been formed. The process involves the automatic mechanical removal of sprayed ring components from a mould. Both the structure and properties of powdered material along with the GDS technology itself were studied. The main spraying and mould parameters were found to achieve high durability of moulds, which allowed the realization of a large scale GDS forming technology.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.931

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)0.0010.000

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 head0.004
GPT teacher head0.185
Teacher spread0.181 · 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