{"id":"W4386072889","doi":"10.11159/icmie23.141","title":"Design and Testing of a Pneumatic Grain Aspirator for Efficient Separation of Impurities","year":2023,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering","topic":"Cyclone Separators and Fluid Dynamics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Aspirator; Impurity; Separation (statistics); Materials science; Computer science; Mechanical engineering; Engineering; Chemistry; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001253896,0.0004016677,0.0005312559,0.0003177741,0.0004653241,0.0007597423,0.001150423,0.0009953926,0.001550784],"category_scores_gemma":[0.00150182,0.0003471907,0.000603897,0.0001732165,0.0004689342,0.0006392344,0.0005378,0.0003728715,0.0006473829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000490139,"about_ca_system_score_gemma":0.00130128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001113084,"about_ca_topic_score_gemma":0.0009480556,"domain_scores_codex":[0.9991701,0.0001281783,0.00008640071,0.000132863,0.0004201522,0.00006244106],"domain_scores_gemma":[0.9991601,0.0002405952,0.0001171235,0.0001026942,0.0003130447,0.00006655814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008029476,0.000307299,0.009063968,0.002209237,0.0001089273,0.0008547749,0.0007606144,0.09680243,0.7754163,0.002609198,0.002237485,0.1088269],"study_design_scores_gemma":[0.0003017305,0.003900535,0.01097363,0.0001364376,0.0001631803,0.0008027806,0.0002762126,0.3109358,0.6313197,0.0006048155,0.04044366,0.0001415834],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5737586,0.001339913,0.4098951,0.0005616763,0.0002319484,0.001624664,0.0005953467,0.003226839,0.008765977],"genre_scores_gemma":[0.8827779,0.0003789192,0.1115042,0.00009839592,0.00002140005,0.0005061385,0.0003078827,0.00009889905,0.004306279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001550784,"threshold_uncertainty_score":0.006631374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01210774048048509,"score_gpt":0.2204064154399154,"score_spread":0.2082986749594303,"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."}}