{"id":"W2960158485","doi":"10.1145/3306346.3322978","title":"Creating impactful characters","year":2019,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Winter Sports Injuries and Performance","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Institute for Computing, Information and Cognitive Systems; Killam Trusts; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Acceleration; Motion capture; Computer science; Jump; Motion (physics); Accelerometer; Computer vision; Artificial intelligence; Inertial measurement unit; Dynamics (music); Simulation; Motion analysis; Acoustics; Physics","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":[0.0004437615,0.001538537,0.0004170734,0.000969697,0.0006747301,0.001990149,0.001142729,0.0008169929,0.02853635],"category_scores_gemma":[0.002712791,0.00045752,0.0007754224,0.0005284285,0.0005689678,0.001840499,0.003607619,0.0006122633,0.005937297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002912137,"about_ca_system_score_gemma":0.000194371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002333224,"about_ca_topic_score_gemma":0.000557799,"domain_scores_codex":[0.9994321,0.0001050109,0.00002492623,0.0001398313,0.0002255582,0.00007253236],"domain_scores_gemma":[0.9993011,0.0002092561,0.0000470405,0.0001806583,0.0001294499,0.0001324695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005701866,0.0002329874,0.004666209,0.001536522,0.0001412993,0.001934179,0.003437235,0.01327458,0.124361,0.01769914,0.04010642,0.7920401],"study_design_scores_gemma":[0.0001318045,0.0009819977,0.01789263,0.0005720381,0.0002539741,0.005064187,0.002993546,0.1060647,0.1252888,0.01644859,0.7240912,0.0002165591],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1764647,0.002226745,0.657046,0.0008782863,0.001804164,0.001365004,0.001859203,0.01883063,0.1395253],"genre_scores_gemma":[0.549188,0.001963948,0.3587416,0.0003987815,0.0003833421,0.0007556643,0.002931082,0.00407986,0.08155785],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02853635,"threshold_uncertainty_score":0.09546357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.013273347291997,"score_gpt":0.2706079183904091,"score_spread":0.2573345710984121,"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."}}