{"id":"W1986833787","doi":"10.1167/13.9.94","title":"Adaptation aftereffect from faces using the bubbles technique","year":2013,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Aesthetic Perception and Analysis","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Percept; Adaptation (eye); Facial expression; Psychology; Perception; Expression (computer science); Face (sociological concept); Cognitive psychology; Orientation (vector space); Perspective (graphical); Communication; Artificial intelligence; Computer science; Mathematics; Neuroscience; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002129074,0.00005611176,0.00009868282,0.00007165415,0.0001005242,0.00008472173,0.0001516111,0.00003106982,0.0003663565],"category_scores_gemma":[0.0001106484,0.00002935317,0.00009062685,0.000125819,0.00004164449,0.000293167,0.00002165046,0.0001186453,0.00003820041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002299066,"about_ca_system_score_gemma":0.00001501192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007306498,"about_ca_topic_score_gemma":0.000002193281,"domain_scores_codex":[0.9992267,0.0001726291,0.0002064321,0.00007371303,0.0002533464,0.00006715956],"domain_scores_gemma":[0.9995272,0.00006087806,0.0002264736,0.00009126746,0.00005725648,0.00003688493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000006725846,0.00001940821,0.00009162934,7.883639e-7,9.583903e-7,0.000002726156,0.0002129432,0.0003758779,0.9747614,0.000007177156,0.0001824477,0.02433797],"study_design_scores_gemma":[0.001320724,0.001226036,0.07867898,0.000811071,0.0002288654,0.0005552188,0.003998078,0.2960801,0.5938151,0.0127727,0.009948201,0.0005649284],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9479334,0.00004972039,0.05101079,0.0007886574,0.00006249369,0.00007573851,8.140386e-7,0.000007236736,0.00007117601],"genre_scores_gemma":[0.9966789,0.0000849233,0.002841068,0.0002861063,0.00006243214,0.000001604134,1.4232e-7,0.000004747857,0.00004000405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3809463,"threshold_uncertainty_score":0.4011347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04258485560768239,"score_gpt":0.3221759677955426,"score_spread":0.2795911121878602,"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."}}