{"id":"W1977606836","doi":"10.1167/10.6.22","title":"Frames of reference for biological motion and face perception","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Queen's University","funders":"York University; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Biological motion; Reference frame; Perception; Stimulus (psychology); Frame of reference; Computer vision; Artificial intelligence; Observer (physics); Visual perception; Computer science; Communication; Rendering (computer graphics); Psychology; Motion (physics); Cognitive psychology; Frame (networking); Physics; Neuroscience; Classical mechanics","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":[0.0004794209,0.0003746552,0.000191804,0.0003747188,0.0003644176,0.0006629969,0.0003055909,0.0002819712,0.00228212],"category_scores_gemma":[0.002292123,0.0001338996,0.0001678938,0.0002909093,0.0005684394,0.0007721423,0.0004949102,0.0004063569,0.0003063625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004988358,"about_ca_system_score_gemma":0.0003076618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002481481,"about_ca_topic_score_gemma":0.004481608,"domain_scores_codex":[0.9997907,0.00008984365,0.00000663363,0.00004051486,0.00004591308,0.00002634812],"domain_scores_gemma":[0.9995391,0.0001502272,0.00008680957,0.00007174583,0.0001174528,0.0000345301],"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":[0.001157039,0.00005127986,0.01185793,0.0003663624,0.0000488058,0.000711853,0.002727371,0.004936699,0.6779467,0.14694,0.001949738,0.1513062],"study_design_scores_gemma":[0.0002194371,0.00170623,0.2528399,0.0006021721,0.0003259567,0.002357509,0.004397084,0.05432448,0.423162,0.1935899,0.06610452,0.0003708025],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7836215,0.009146848,0.1718362,0.0007962649,0.0002778788,0.00006110636,0.0002352792,0.0001531503,0.03387171],"genre_scores_gemma":[0.9595187,0.001753442,0.03640036,0.00007040879,0.00004421054,0.00002880591,0.0001265789,0.00004070427,0.002016659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002481481,"threshold_uncertainty_score":0.007634401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09194223531793766,"score_gpt":0.3655756238165302,"score_spread":0.2736333884985926,"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."}}