{"id":"W1997608580","doi":"10.5555/846276.846323","title":"FootSee: an interactive animation system","year":2003,"lang":"en","type":"article","venue":"Symposium on Computer Animation","topic":"Human Motion and Animation","field":"Engineering","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Animation; Avatar; Motion capture; Inverse kinematics; Skeletal animation; Kinematics; Computer animation; Motion (physics); Low latency (capital markets); Virtual reality; Computer graphics (images); Latency (audio); Interface (matter); Computer vision; Artificial intelligence; Computer facial animation; Human–computer interaction; 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":[0.0003523224,0.0009932469,0.0004777158,0.000721053,0.0002911593,0.0007542472,0.001354864,0.0006872657,0.04918966],"category_scores_gemma":[0.001022909,0.0004219583,0.000392822,0.0002717312,0.000179883,0.0009605309,0.001818166,0.0005530308,0.005354726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002235254,"about_ca_system_score_gemma":0.0002551849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001314965,"about_ca_topic_score_gemma":0.001760364,"domain_scores_codex":[0.9997795,0.00002977277,0.0000161373,0.00005216531,0.0000959756,0.00002648169],"domain_scores_gemma":[0.9996798,0.00009662798,0.00001452273,0.00007172938,0.00005236451,0.00008496697],"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":[0.002737914,0.0005330215,0.003269323,0.0005730474,0.0001766661,0.0008522129,0.0006106464,0.01644814,0.1295057,0.005496617,0.198246,0.6415506],"study_design_scores_gemma":[0.001461222,0.001120739,0.009571396,0.0001240224,0.0002037704,0.001913778,0.000223106,0.3231732,0.08280199,0.008464234,0.5706726,0.0002698952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.03936647,0.0005781192,0.6033439,0.0002488249,0.0003441304,0.0007507664,0.006469117,0.3165598,0.03233882],"genre_scores_gemma":[0.4984223,0.00100646,0.3783632,0.0005339418,0.0003831693,0.001818744,0.02585802,0.01408779,0.07952653],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04918966,"threshold_uncertainty_score":0.1645558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01081316991734719,"score_gpt":0.222557858573644,"score_spread":0.2117446886562968,"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."}}