{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000938448,0.0001226273,0.0001795385,0.0001714547,0.0001028088,0.00001769159,0.0001044907,0.00008146434,0.0008904846],"category_scores_gemma":[0.000008674993,0.0001034333,0.0001587429,0.0002492285,0.00003925946,0.0001342412,0.00000220548,0.0003545605,0.0001544803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002424028,"about_ca_system_score_gemma":0.00003696544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003672188,"about_ca_topic_score_gemma":0.00000836466,"domain_scores_codex":[0.9992558,0.000006713301,0.0001771261,0.0001771189,0.0001827014,0.0002004755],"domain_scores_gemma":[0.9991736,0.00004722142,0.00004755022,0.0005815263,0.00004685662,0.0001032796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004667884,0.002760773,0.6862755,0.001389546,0.001843357,0.0001656236,0.01045058,0.0004715296,0.01807774,0.004891319,0.003107869,0.2658983],"study_design_scores_gemma":[0.004095967,0.003386419,0.8810083,0.0009235987,0.000423893,0.0003532293,0.001040148,0.00142861,0.01851399,0.0006904401,0.08728758,0.0008477926],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915487,0.00002817023,0.001596036,0.001872473,0.000483746,0.000222797,0.00001403708,0.00009725647,0.004136772],"genre_scores_gemma":[0.9948526,0.0001798377,0.0005155767,0.001927382,0.00006686197,0.000008862229,0.0000120349,0.00002113844,0.002415711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2650505,"threshold_uncertainty_score":0.9750181,"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."}}