{"id":"W3003076508","doi":"10.24908/iqurcp.10641","title":"7. Shape and Motion Integration in People Perception Depends on the Action of the Performer","year":2018,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Motion (physics); Perception; Action (physics); Performing arts; Object (grammar); Biological motion; Kinematics; Communication; Artificial intelligence; Motion capture; Computer vision; Psychology; Computer science; Physics; Visual arts; Art; Classical mechanics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008295201,0.0003971205,0.0003337618,0.0004171732,0.0003608743,0.001564003,0.0002876458,0.0009071559,0.005955875],"category_scores_gemma":[0.00375168,0.0004031901,0.0006023171,0.0001846414,0.0007005993,0.001787446,0.0009194345,0.0004958667,0.0005120719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000278363,"about_ca_system_score_gemma":0.0001784329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001631268,"about_ca_topic_score_gemma":0.001119913,"domain_scores_codex":[0.9994774,0.0001047368,0.00002924014,0.000157276,0.000153216,0.00007820128],"domain_scores_gemma":[0.9990585,0.0003315292,0.000153717,0.000141816,0.0001761598,0.000138267],"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":[0.002196646,0.0002013268,0.1448251,0.0005522222,0.0002383516,0.0008305098,0.007912162,0.002437836,0.7196666,0.006770281,0.00140896,0.1129601],"study_design_scores_gemma":[0.00007168487,0.0004712767,0.9357339,0.0001005414,0.0001765929,0.0007286657,0.002929054,0.00818565,0.04234637,0.007089777,0.002086051,0.00008040576],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9695524,0.0003293591,0.01455449,0.00030844,0.00003948792,0.00003947719,0.0001137819,0.0001285165,0.01493395],"genre_scores_gemma":[0.995698,0.00007427522,0.003420121,0.00006160264,0.00001265719,0.00001521684,0.00005518613,0.00002785576,0.000635048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005955875,"threshold_uncertainty_score":0.0199244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1470669104366305,"score_gpt":0.3956191493023162,"score_spread":0.2485522388656857,"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."}}