{"id":"W3137056057","doi":"10.1037/bne0000447","title":"Viewing orbitofrontal cortex contributions to decision-making through the lens of object recognition.","year":2021,"lang":"en","type":"review","venue":"Behavioral Neuroscience","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Orbitofrontal cortex; Psychology; Cognitive psychology; Neuroscience; Cognitive neuroscience of visual object recognition; Object (grammar); Prefrontal cortex; Cognition; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003975226,0.0005226802,0.001224269,0.0002403618,0.0008104703,0.0002837045,0.001041347,0.0002401553,0.0003903752],"category_scores_gemma":[0.002782416,0.0003841518,0.0007494847,0.002456545,0.0004830302,0.0005949454,0.0004309999,0.0007484512,0.0003576062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002001785,"about_ca_system_score_gemma":0.0005767065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003254478,"about_ca_topic_score_gemma":0.00001795941,"domain_scores_codex":[0.9952938,0.0007365089,0.001068542,0.001291171,0.0009644972,0.00064549],"domain_scores_gemma":[0.9972665,0.001006624,0.0005528571,0.0007629396,0.0002669938,0.0001441396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006558581,0.0002705565,0.000001617857,0.0002652935,0.000001514013,0.00006756154,0.0003342015,0.00000517104,0.006854482,0.0000956951,0.0005930052,0.9915044],"study_design_scores_gemma":[0.0001562591,0.0002417482,0.0000621061,0.0110876,0.0003759667,0.0006416426,0.0001115024,0.00001726306,0.0004941573,0.0001028973,0.9860539,0.0006549007],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.008979397,0.9591768,0.006804761,0.0003170625,0.009630258,0.00571732,0.007651814,0.0004193588,0.001303209],"genre_scores_gemma":[0.01426915,0.9832612,0.0005596812,0.00128074,0.0001514638,0.0002468177,0.00005094354,0.00006443948,0.0001156199],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9908494,"threshold_uncertainty_score":0.9998611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2441484726498313,"score_gpt":0.4559809749394925,"score_spread":0.2118325022896612,"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."}}