{"id":"W2001501176","doi":"10.3389/fpsyg.2014.00512","title":"Affective and contextual values modulate spatial frequency use in object recognition","year":2014,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Psychology; Object (grammar); Cognitive neuroscience of visual object recognition; Perception; Representation (politics); Cognitive psychology; Flexibility (engineering); Visual processing; Identification (biology); Visual perception; Task (project management); Artificial intelligence; Pattern recognition (psychology); Communication; Computer science; Mathematics; Statistics","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":[0.0002970195,0.0001296434,0.0002095299,0.0003554617,0.00004492056,0.00002706902,0.00007676762,0.0001722763,0.0001133485],"category_scores_gemma":[0.0005966706,0.0001359023,0.00002984176,0.0001999666,0.0002021289,0.0002664646,0.00001590301,0.000257011,0.00008603413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004174732,"about_ca_system_score_gemma":0.000007838432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002310472,"about_ca_topic_score_gemma":0.0004621934,"domain_scores_codex":[0.9982358,0.0007209224,0.0002124579,0.0004943091,0.00008739249,0.0002491732],"domain_scores_gemma":[0.9995805,0.0001499072,0.0000624098,0.0001368785,0.00001870224,0.00005157816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003770904,0.0002233826,0.1420466,0.0000156182,0.000005030392,0.00002438173,0.001393876,0.000007310623,0.06020667,0.00007956484,0.002649952,0.7929706],"study_design_scores_gemma":[0.006468961,0.0008756862,0.7988499,0.0001192251,0.00001443129,0.00009482441,0.0003554241,0.008837589,0.006315713,0.1762358,0.001208004,0.0006245128],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9674188,0.00003002583,0.02641593,0.0001827787,0.001749658,0.0002891793,0.00002083611,0.0000443524,0.003848458],"genre_scores_gemma":[0.9955746,0.0002816827,0.0025126,0.001466955,0.00006246474,0.00003351546,0.00001388027,0.00001408312,0.00004023448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7923461,"threshold_uncertainty_score":0.5541934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0466762599877319,"score_gpt":0.3099814378726015,"score_spread":0.2633051778848696,"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."}}