{"id":"W4402438896","doi":"10.11159/htff24.198","title":"An Efficient Platform to Capture Flow Features In Industrial Applications","year":2024,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Flow (mathematics); Mechanics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002059914,0.0002126026,0.0002645989,0.000236285,0.00003882171,0.0001968937,0.0002212194,0.0001968585,0.00001276548],"category_scores_gemma":[0.00003733686,0.0001644658,0.00005865641,0.0005200789,0.00001520027,0.00009247343,0.00006420824,0.0003669583,0.000002849403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008342036,"about_ca_system_score_gemma":0.000009402617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001247798,"about_ca_topic_score_gemma":0.000002989008,"domain_scores_codex":[0.9989643,0.000002527981,0.0003220882,0.0002741253,0.0001964537,0.0002405511],"domain_scores_gemma":[0.9996571,0.00003918743,0.00002861564,0.0001206353,0.00003545737,0.0001190253],"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":[0.00006171938,0.00001874934,9.872933e-7,0.0002168655,0.00001824916,6.890686e-7,0.00002380158,0.01574338,0.9771532,0.003692205,0.001096169,0.001973918],"study_design_scores_gemma":[0.0002602776,0.00003484709,0.000003054332,0.0005773634,0.00001653921,0.000007968851,0.00004382486,0.04391676,0.9463224,0.00005634011,0.008557563,0.0002029996],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957617,0.00002613521,0.00002668227,0.00007042193,0.002808323,0.0006511947,0.00004089588,0.0003484301,0.0002662522],"genre_scores_gemma":[0.9988036,0.000005868302,0.0003002265,0.00001472793,0.0006158571,0.0001566373,0.000002815683,0.00004388127,0.00005636893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03083081,"threshold_uncertainty_score":0.6706719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008679791804270065,"score_gpt":0.2161888303001475,"score_spread":0.2075090384958774,"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."}}