{"id":"W3048907270","doi":"10.11947/j.jggs.2020.0201","title":"An Investigation of Optimal Machine Learning Methods for the Prediction of ROTI","year":2020,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Machine learning; Artificial intelligence; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001267134,0.0001536781,0.000459419,0.0001979322,0.0001060541,0.0001683313,0.0007834846,0.00007708369,0.00040545],"category_scores_gemma":[0.0002769018,0.0001235444,0.0001390269,0.0004928078,0.0000534405,0.0008729279,0.0000737298,0.0002697961,7.340743e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002916253,"about_ca_system_score_gemma":0.00002896395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002425161,"about_ca_topic_score_gemma":0.00000777196,"domain_scores_codex":[0.99843,0.0003058974,0.0007143476,0.000160541,0.0002490475,0.0001401355],"domain_scores_gemma":[0.9987038,0.000343962,0.0004515205,0.0001871915,0.0001828042,0.0001307711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001307863,0.00001495934,0.03796823,0.0001941955,0.0002035839,2.944289e-7,0.0007212436,0.2083726,0.7235661,0.00002086454,0.0005785656,0.02822862],"study_design_scores_gemma":[0.0005447435,0.00004862285,0.04846109,0.0001099295,0.00009189664,0.000002999544,0.0002236263,0.7600675,0.1872294,0.0001281882,0.002970137,0.0001219601],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6639514,0.01182455,0.3216369,0.0001547632,0.0008285331,0.001019079,0.00007890719,0.000139503,0.0003663862],"genre_scores_gemma":[0.9963133,0.0007703087,0.002589207,0.00004263059,0.0001645469,0.00005346139,0.00001022479,0.00003808933,0.0000181727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5516948,"threshold_uncertainty_score":0.5037994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2032825761362911,"score_gpt":0.5092651037796367,"score_spread":0.3059825276433456,"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."}}