{"id":"W2151621026","doi":"10.1142/s0219843612500028","title":"HUMANOID FALL AVOIDANCE USING A MIXTURE OF STRATEGIES","year":2012,"lang":"en","type":"article","venue":"International Journal of Humanoid Robotics","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Humanoid robot; Computer science; Robot; Simulation; Overhead (engineering); Ankle; Falling (accident); Artificial intelligence","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":[0.0002530981,0.000143792,0.0002339615,0.0002229295,0.00003584262,0.00005240234,0.0003829617,0.00008431217,0.0000244047],"category_scores_gemma":[0.0000458471,0.0001279188,0.0001556973,0.00007772643,0.00008927235,0.000534796,0.00004069121,0.0002623309,0.000004547621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001054487,"about_ca_system_score_gemma":0.00007605301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002543459,"about_ca_topic_score_gemma":0.000002264608,"domain_scores_codex":[0.998629,0.00002725998,0.000635838,0.00005752433,0.0004552795,0.000195096],"domain_scores_gemma":[0.9988442,0.00006826797,0.0002926977,0.0001179285,0.000591712,0.00008518493],"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":[0.00001325296,0.000121002,0.001938358,0.00005854826,0.0001879563,0.000007702673,0.001207784,0.9540389,0.02841906,0.01343269,0.0003259417,0.0002487714],"study_design_scores_gemma":[0.01308989,0.00237337,0.09430618,0.00461305,0.001509665,0.00392853,0.01451197,0.6068798,0.1376181,0.08369019,0.03215705,0.005322202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7589718,0.00403368,0.229371,0.0002125537,0.005441952,0.0001114002,0.0000174491,0.00004237679,0.001797813],"genre_scores_gemma":[0.9625205,0.0001331763,0.0366463,0.00002757437,0.0005873068,4.237218e-7,0.000002544409,0.0000273383,0.00005485471],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3471591,"threshold_uncertainty_score":0.5216376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01506253226738008,"score_gpt":0.269295139290844,"score_spread":0.254232607023464,"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."}}