{"id":"W3005999075","doi":"10.2316/j.2020.206-0151","title":"CENTRAL PATTERN GENERATOR BASED MOTION CONTROL OF HOPPING ROBOT FOR GROUND LEVEL ACCLIMATIZATION","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Central pattern generator; Robot; Generator (circuit theory); Jumping; Computer science; Motion control; Control theory (sociology); Control (management); Artificial intelligence; Acoustics; Physics; Geology; Rhythm; Power (physics)","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":[0.0001474481,0.0002538466,0.0002090861,0.0001502304,0.0001734629,0.0001703106,0.0004599862,0.00021473,0.001098805],"category_scores_gemma":[0.0002568876,0.00007864145,0.0001270154,0.0001298566,0.0001905508,0.0001560993,0.0002535399,0.0002337354,0.0001540757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001126665,"about_ca_system_score_gemma":0.0002905722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001038827,"about_ca_topic_score_gemma":0.001429536,"domain_scores_codex":[0.9999405,0.000009032385,0.000002806767,0.00002023339,0.00001704758,0.00001026257],"domain_scores_gemma":[0.9999143,0.00001797887,0.00001396018,0.000008066901,0.00003498299,0.00001075826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003251964,0.0001693966,0.002762351,0.0003035844,0.00008384181,0.0003227657,0.0002584148,0.1663103,0.383768,0.008468918,0.002763281,0.434464],"study_design_scores_gemma":[0.0000618629,0.0003764327,0.002669119,0.00001562563,0.00003390932,0.0001663293,0.00003192192,0.9672185,0.02500101,0.002096626,0.002309107,0.00001951085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08335957,0.0002001845,0.911159,0.00007999134,0.00007981082,0.00007624809,0.00003789082,0.0009186761,0.004088708],"genre_scores_gemma":[0.9242485,0.00006782341,0.07308996,0.00004344889,0.00001410527,0.000103032,0.00004688877,0.00002898923,0.00235729],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001098805,"threshold_uncertainty_score":0.003675878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02433279487973472,"score_gpt":0.232616770011273,"score_spread":0.2082839751315383,"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."}}