{"id":"W2076806230","doi":"10.1145/2366145.2366173","title":"Terrain runner","year":2012,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Human Motion and Animation","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Ministry of Education - Singapore","keywords":"Computer science; Terrain; Continuation; Obstacle; Process (computing); Control theory (sociology); Motion (physics); Trajectory; Simulation; Artificial intelligence; Computer vision; Control (management); Law","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":[0.0001351774,0.0006663082,0.0003230356,0.0002073458,0.0004433678,0.0006882574,0.0008594606,0.0006042225,0.03927393],"category_scores_gemma":[0.0005636471,0.0001793827,0.0004185666,0.0001217018,0.0003346651,0.0009798295,0.001357315,0.0007720974,0.00944972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002121051,"about_ca_system_score_gemma":0.0003222924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001060846,"about_ca_topic_score_gemma":0.002358157,"domain_scores_codex":[0.9998833,0.00002054457,0.00000478831,0.00004478873,0.00003052992,0.00001609498],"domain_scores_gemma":[0.9998728,0.00002532765,0.000008469811,0.00003251614,0.00002185899,0.0000390977],"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":[0.000790741,0.0005780993,0.008073493,0.0008157445,0.00009445829,0.001884777,0.002199411,0.1483718,0.1528838,0.07826721,0.03076781,0.5752729],"study_design_scores_gemma":[0.0001264428,0.001631481,0.008573084,0.0002791022,0.0000721306,0.00279945,0.001257746,0.4550314,0.05634005,0.03647343,0.4372737,0.0001420075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2063987,0.0005362019,0.5788055,0.0007774737,0.0004399334,0.0003896092,0.001043701,0.009307498,0.2023014],"genre_scores_gemma":[0.6726217,0.0006279525,0.2068231,0.0003338429,0.00004912916,0.0002093124,0.002210212,0.0007880643,0.1163366],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03927393,"threshold_uncertainty_score":0.1313844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0210172069993978,"score_gpt":0.2350150555078467,"score_spread":0.2139978485084489,"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."}}