{"id":"W4391190137","doi":"10.1299/jsmermd.2023.2p1-d06","title":"Evaluation of SafeML by robot risk assessment description model","year":2023,"lang":"en","type":"article","venue":"The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cybernet Systems Corporation (Canada)","funders":"","keywords":"Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002418143,0.0002701212,0.0004105681,0.0001915192,0.0001321989,0.00009863856,0.0003085035,0.0001572223,0.000007850166],"category_scores_gemma":[0.00006870542,0.0002180282,0.00008363176,0.0003562412,0.00007732211,0.00024961,0.00009030526,0.0003087752,0.00000726941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001098102,"about_ca_system_score_gemma":0.0001098954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002143383,"about_ca_topic_score_gemma":0.00000351178,"domain_scores_codex":[0.9978378,0.00002973298,0.0005534012,0.0002750946,0.0009245415,0.000379362],"domain_scores_gemma":[0.9981658,0.00004404837,0.0002943689,0.0001802931,0.00122402,0.0000914106],"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":[0.000008442548,0.00003944974,0.00005032411,0.0001284763,0.0001094876,6.475275e-8,0.000835921,0.8878993,0.03137205,0.07605711,0.001341046,0.002158322],"study_design_scores_gemma":[0.0005057621,0.000190946,0.0001688638,0.0001548772,0.0002279673,0.000001289753,0.002018617,0.9705298,0.002827524,0.02313848,0.00001892388,0.0002169391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8935922,0.0009551066,0.09169506,0.001237874,0.0007287904,0.00190562,0.0003962676,0.0006393635,0.008849693],"genre_scores_gemma":[0.9958583,0.001831523,0.002027276,0.000009980671,0.00002721925,0.00003754216,0.00002810352,0.00004463839,0.000135484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.102266,"threshold_uncertainty_score":0.8890933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04020021181928964,"score_gpt":0.2712569910417681,"score_spread":0.2310567792224785,"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."}}