{"id":"W4294791124","doi":"10.31399/asm.cp.itsc2007p0190","title":"Numerical Simulation of the Solution Precursor Plasma Spraying Process","year":2007,"lang":"en","type":"article","venue":"Thermal spray","topic":"Aerosol Filtration and Electrostatic Precipitation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Solution precursor plasma spray; Materials science; Jet (fluid); Ceramic; Plasma; Thermal spraying; Particle (ecology); Atmospheric-pressure plasma; Gas dynamic cold spray; Precipitation; Substrate (aquarium); Process (computing); Coating; Mechanics; Chemical engineering; Composite material; Meteorology; Physics; Engineering; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000320037,0.0004289477,0.0006546495,0.0004853698,0.0006064779,0.00073785,0.0006386407,0.001579367,0.00452156],"category_scores_gemma":[0.001349574,0.0002975905,0.000577968,0.0004811553,0.0006011351,0.0003537771,0.0004611845,0.0005180807,0.0003140928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001091088,"about_ca_system_score_gemma":0.001011907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01920927,"about_ca_topic_score_gemma":0.006605989,"domain_scores_codex":[0.9998496,0.00002996909,0.000007123396,0.0000211946,0.00005336009,0.00003865357],"domain_scores_gemma":[0.9992653,0.0004292278,0.00005627356,0.00003447747,0.000165589,0.00004924546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004336729,0.00002912911,0.0007967148,0.00003002615,0.000007621367,0.00006569876,0.00003204627,0.9937927,0.001512806,0.001836949,0.0002349929,0.001617969],"study_design_scores_gemma":[0.00001012045,0.00000976369,0.0001296571,0.000002396877,0.000001463864,0.000005280187,0.000008029485,0.999111,0.0002921082,0.0001969567,0.0002304658,0.000002761892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8039601,0.000593469,0.1288751,0.0009361976,0.0002538314,0.0002406408,0.001648607,0.0008471188,0.0626448],"genre_scores_gemma":[0.9697737,0.0001494706,0.02334056,0.00007722821,0.00001453217,0.0001920113,0.0005313827,0.00005271395,0.005868417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01920927,"threshold_uncertainty_score":0.03819489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01138824755829111,"score_gpt":0.2518374178108496,"score_spread":0.2404491702525585,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}