{"id":"W2756272268","doi":"10.1145/3119881.3119891","title":"Effects of animation retargeting on perceived action outcomes","year":2017,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Retargeting; Motion capture; Animation; Motion (physics); Kinematics; Perception; Action (physics); Computer science; Computer vision; Artificial intelligence; Computer animation; Character animation; Set (abstract data type); Body shape; Communication; Psychology; Computer graphics (images); 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":[0.0009330124,0.0004212176,0.0002597405,0.0002369141,0.0001539928,0.00049486,0.0002249146,0.0003834392,0.001850107],"category_scores_gemma":[0.0113686,0.0002397653,0.0001632697,0.00009320502,0.000429591,0.000269685,0.0006759388,0.0004406037,0.0001132117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002016476,"about_ca_system_score_gemma":0.0001026622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007067272,"about_ca_topic_score_gemma":0.0007655975,"domain_scores_codex":[0.999365,0.0002520651,0.000052633,0.0001239959,0.0001347604,0.00007150808],"domain_scores_gemma":[0.9935261,0.004671476,0.0008119736,0.0003734007,0.000258607,0.0003584868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.006227319,0.0002617966,0.02440024,0.0002272805,0.000095868,0.0003396022,0.002129271,0.002027432,0.9418858,0.0001854093,0.0000864674,0.02213341],"study_design_scores_gemma":[0.0001667505,0.006778819,0.8825457,0.00005099327,0.0002257832,0.0004776465,0.001105865,0.007262901,0.100301,0.000437398,0.000571179,0.00007611726],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989263,0.00003114163,0.0004859043,0.000008982571,0.000005044958,0.000009187074,0.0000228392,0.00001298904,0.0004975882],"genre_scores_gemma":[0.9987649,0.00002290425,0.0008993603,0.000009297642,0.00000311924,0.00001374337,0.00003693749,0.00001852423,0.0002312972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001850107,"threshold_uncertainty_score":0.006189167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02284357331543003,"score_gpt":0.2715934011352329,"score_spread":0.2487498278198029,"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."}}