{"id":"W4200400891","doi":"10.1145/3478513.3480527","title":"SuperTrack","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Human Motion and Animation","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ubisoft (Canada)","funders":"Mitacs","keywords":"Computer science; Task (project management); Differentiable function; Sensitivity (control systems); Character (mathematics); Tracking (education); Control (management); Quality (philosophy); Tracking error; Mathematical optimization; Function (biology); Artificial intelligence; Motion (physics); Algorithm; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007791203,0.0006570128,0.0007982894,0.0005480936,0.0007968006,0.001114887,0.001872383,0.001146787,0.03351181],"category_scores_gemma":[0.003206675,0.0004702373,0.0006592957,0.0004807477,0.0007213861,0.002087428,0.002888927,0.001363622,0.00904825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005308244,"about_ca_system_score_gemma":0.001006705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002494944,"about_ca_topic_score_gemma":0.0045672,"domain_scores_codex":[0.9993788,0.000093599,0.0000234931,0.0002590179,0.0001771477,0.0000678825],"domain_scores_gemma":[0.9988371,0.0004184023,0.00006583839,0.000412077,0.0001825387,0.00008411611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008850587,0.0002960041,0.003200008,0.0003706048,0.0001052032,0.0004411062,0.0004227696,0.3320066,0.01719337,0.1007112,0.04752688,0.4968413],"study_design_scores_gemma":[0.00005430673,0.0001345392,0.0003999722,0.00003342723,0.00002214151,0.0001755649,0.00008011011,0.920598,0.006887967,0.03610735,0.03548308,0.00002341524],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01549874,0.000201999,0.9507551,0.0003058949,0.0004242047,0.0001150495,0.0004945887,0.00595529,0.02624923],"genre_scores_gemma":[0.3583435,0.0003984359,0.5727772,0.000938846,0.0001776637,0.0004710805,0.003527768,0.002737918,0.06062758],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03351181,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02091339084471841,"score_gpt":0.2258401184467532,"score_spread":0.2049267276020348,"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."}}