{"id":"W3106439297","doi":"10.1115/detc2001/dac-21013","title":"Posture Prediction Versus Inverse Kinematics","year":2001,"lang":"en","type":"article","venue":"","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Kinematics; Inverse kinematics; Torso; Position (finance); Computer science; Degrees of freedom (physics and chemistry); Point (geometry); Orientation (vector space); Inverse; Robot kinematics; Kinematics equations; Control theory (sociology); Artificial intelligence; Robot; Mathematics; Geometry; Mobile robot","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009326107,0.0007681348,0.000881316,0.0006199574,0.0002857344,0.0008737156,0.0005794413,0.0009331622,0.002547246],"category_scores_gemma":[0.00480337,0.0003284627,0.0004815283,0.0004679349,0.001194894,0.00121918,0.0006779488,0.0005719428,0.0006978582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004097301,"about_ca_system_score_gemma":0.000443693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002273921,"about_ca_topic_score_gemma":0.001266115,"domain_scores_codex":[0.9993179,0.0002675211,0.00004218194,0.0001527651,0.0001592246,0.00006042498],"domain_scores_gemma":[0.9973725,0.001634011,0.0002771337,0.000310817,0.0003450028,0.00006043303],"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":[0.000230176,0.00006256285,0.003136215,0.0001177111,0.0000316005,0.00008939658,0.00006940805,0.8056386,0.005945302,0.03118542,0.0007679809,0.1527257],"study_design_scores_gemma":[0.00000820286,0.00009345551,0.0008128422,0.00002967381,0.000008696224,0.00003982125,0.00001676944,0.9782853,0.001589022,0.01871446,0.0003900309,0.00001176566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04338527,0.0003711371,0.9502509,0.0002685521,0.00005108108,0.00003568521,0.00004283712,0.000363059,0.005231486],"genre_scores_gemma":[0.883049,0.0003669208,0.1135638,0.00005666748,0.00007383844,0.00007503105,0.0001205206,0.0000620167,0.002632192],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002547246,"threshold_uncertainty_score":0.008521318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03276094881377407,"score_gpt":0.2530729577250889,"score_spread":0.2203120089113148,"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."}}