{"id":"W4411569957","doi":"10.2316/j.2025.206-1208","title":"JERK-CONTINUOUS ONLINE TRAJECTORY PLANNING AND FEEDFORWARD CONTROL FOR FLEXIBLE JOINT ROBOTS, 1-8.","year":2025,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Feed forward; Jerk; Trajectory; Robot; Joint (building); Computer science; Control theory (sociology); Control (management); Control engineering; Engineering; Artificial intelligence; Physics; Structural engineering","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":[0.0001936449,0.00009718337,0.0002006834,0.0002149535,0.00003755104,0.00009276937,0.00008323793,0.00006100555,0.000002698034],"category_scores_gemma":[0.00005532816,0.00008941982,0.00005662881,0.0000325895,0.00001534378,0.0001470983,0.00001406464,0.0001046825,2.053383e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005063875,"about_ca_system_score_gemma":0.00002686027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001828058,"about_ca_topic_score_gemma":0.000001690312,"domain_scores_codex":[0.9992928,0.000008659394,0.0003851307,0.00007049806,0.0001465464,0.00009635092],"domain_scores_gemma":[0.999507,0.00008148083,0.0001272043,0.00004121056,0.0001989113,0.000044195],"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":[0.00002454163,0.00002288605,0.0002552799,0.00004594012,0.0001714044,0.000005106143,0.000104736,0.9686738,0.001803588,0.01285465,0.0002803521,0.01575766],"study_design_scores_gemma":[0.001302192,0.00007188883,0.005106002,0.0002316548,0.00006049592,0.00004997291,0.0001117633,0.9861082,0.0002008973,0.006462455,0.0002037451,0.00009066954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02319534,0.0008012498,0.9739206,0.0006739253,0.001131346,0.0001013527,0.00001638386,0.00004577724,0.0001140682],"genre_scores_gemma":[0.7899453,0.000221361,0.2091998,0.0001871675,0.0002546279,0.000003149158,0.00001848859,0.00001772703,0.0001523312],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.76675,"threshold_uncertainty_score":0.3646435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01107979786662072,"score_gpt":0.2531739825636328,"score_spread":0.242094184697012,"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."}}