{"id":"W3164168863","doi":"10.11159/ffhmt21.121","title":"An Innovational, Collision Model and Data Set Generation at NovelTest-Rig for Validation of Numerical Model in the Frame of MachineLearning","year":2021,"lang":"en","type":"article","venue":"Proceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Frame (networking); Computer science; Set (abstract data type); Collision; Test set; Test (biology); Artificial intelligence; Data modeling; Test data; Programming language; Software engineering","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":[0.001330149,0.0008096794,0.0005928978,0.0008443161,0.0007576043,0.0009712494,0.001836761,0.001007852,0.00837444],"category_scores_gemma":[0.002429408,0.0003651825,0.000727193,0.0008924089,0.0006382354,0.0008736764,0.0009390474,0.001225245,0.00148502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009259559,"about_ca_system_score_gemma":0.001214758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008198322,"about_ca_topic_score_gemma":0.006781525,"domain_scores_codex":[0.9992236,0.0001291918,0.00005294006,0.0001421599,0.0003798892,0.0000722698],"domain_scores_gemma":[0.9988431,0.0003481835,0.00006604606,0.0002857954,0.0003975997,0.00005929427],"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":[0.0008075798,0.0007336826,0.014974,0.0005650196,0.000100003,0.0004864694,0.0003376031,0.8175769,0.02371914,0.0069279,0.01241143,0.1213602],"study_design_scores_gemma":[0.00004188864,0.0001584256,0.002436403,0.00002297796,0.00001065211,0.00006367864,0.00005415806,0.9736505,0.01778805,0.001175477,0.004567994,0.00002978354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3759349,0.0006833315,0.5762166,0.000561493,0.0005043856,0.001075364,0.01056304,0.01819216,0.01626865],"genre_scores_gemma":[0.7926142,0.0001616905,0.1940883,0.00008722822,0.00001745897,0.0007737881,0.007814865,0.0005228834,0.003919502],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00837444,"threshold_uncertainty_score":0.02801532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06238801667888023,"score_gpt":0.2912444889474614,"score_spread":0.2288564722685812,"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."}}