{"id":"W2138349856","doi":"10.1068/p7265","title":"Viewpoint and Pose in Body-Form Adaptation","year":2013,"lang":"en","type":"article","venue":"Perception","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Viewpoints; Adaptation (eye); Perception; Cognitive psychology; Psychology; Face (sociological concept); Artificial intelligence; Communication; Computer vision; Computer science; Physics; Neuroscience; Acoustics","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":[0.0002001699,0.0003787179,0.0002314052,0.0001552067,0.0001217481,0.0003347471,0.000213335,0.000271375,0.003007409],"category_scores_gemma":[0.00174273,0.0002091954,0.0003682788,0.0001001443,0.0004769714,0.0004038835,0.0005196329,0.0004452038,0.0002904562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000179244,"about_ca_system_score_gemma":0.0001380779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008406414,"about_ca_topic_score_gemma":0.0007657084,"domain_scores_codex":[0.9998398,0.0000387346,0.000007875687,0.00003983502,0.00004729696,0.00002645239],"domain_scores_gemma":[0.9997011,0.0001143791,0.00005067359,0.00007393319,0.0000244354,0.0000354779],"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":[0.0003193606,0.00003478656,0.00139917,0.00004273184,0.00001345955,0.00008360275,0.0001087246,0.001422231,0.9777688,0.0003700202,0.00006686626,0.01837038],"study_design_scores_gemma":[0.000107622,0.001425248,0.6468406,0.00004120055,0.00009789492,0.001130097,0.0002922909,0.02183515,0.3202415,0.005232445,0.002657774,0.00009804479],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.976496,0.0004761446,0.01690483,0.00006846149,0.00007007645,0.00005862437,0.00009466147,0.0001253457,0.005705785],"genre_scores_gemma":[0.994262,0.0002638196,0.003900738,0.0000648889,0.00001079891,0.00001830887,0.0001092733,0.00006878142,0.001301407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003007409,"threshold_uncertainty_score":0.01006079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04602028058968718,"score_gpt":0.2719401730560565,"score_spread":0.2259198924663693,"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."}}