{"id":"W2324343215","doi":"10.5430/air.v5n2p55","title":"System identifications by SIRMs models with linear transformation of input variables","year":2016,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Control Systems and Identification","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Benchmark (surveying); Computer science; Transformation (genetics); Sonar; Obstacle; Artificial intelligence; Algorithm; Mathematical optimization; Mathematics","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":[0.001294731,0.0001065506,0.0001720575,0.0002473247,0.0001351576,0.00007057355,0.0002649838,0.00008490575,0.00003621005],"category_scores_gemma":[0.00004857549,0.00007449981,0.00004097564,0.0005942107,0.0001266403,0.0005437022,0.00001360205,0.0001230823,0.000199432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001394784,"about_ca_system_score_gemma":0.0000460696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003269575,"about_ca_topic_score_gemma":0.0001450256,"domain_scores_codex":[0.9982424,0.0001047693,0.0005769485,0.0002045688,0.0005494265,0.0003218416],"domain_scores_gemma":[0.9987426,0.0002078353,0.00005134847,0.0003778987,0.0005362123,0.00008412898],"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":[0.0000513202,0.00007139732,0.00002118487,0.0003038003,0.00005951612,8.654367e-7,0.001262879,0.01882391,0.6717249,0.2320663,0.000528145,0.07508581],"study_design_scores_gemma":[0.00006168504,0.00007106902,0.00001775509,0.0003336382,0.00001307979,0.000003646225,0.00206474,0.456565,0.5327319,0.007076899,0.0008888573,0.0001717096],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07589751,0.000200648,0.9202482,0.0002422307,0.000138601,0.0005276193,0.0000595498,0.0001462099,0.002539432],"genre_scores_gemma":[0.9992068,0.0001081549,0.0002167825,7.881331e-7,0.00006680279,0.0001248336,0.00001396356,0.00002405157,0.0002378167],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9233093,"threshold_uncertainty_score":0.3038014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08706547603729199,"score_gpt":0.3213929739309022,"score_spread":0.2343274978936102,"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."}}