{"id":"W3027896046","doi":"10.1016/j.pneurobio.2020.101824","title":"Neural activity underlying the detection of an object movement by an observer during forward self-motion: Dynamic decoding and temporal evolution of directional cortical connectivity","year":2020,"lang":"en","type":"article","venue":"Progress in Neurobiology","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health; National Science Foundation","keywords":"Magnetoencephalography; Computer science; Artificial intelligence; Neuroscience; Brain activity and meditation; Computer vision; Pattern recognition (psychology); Psychology; Electroencephalography","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":[0.0002232988,0.0001504368,0.000224604,0.00006595645,0.0001933681,0.00002196478,0.0001336485,0.00008613153,0.000002676856],"category_scores_gemma":[0.0001741904,0.0001247675,0.00004865133,0.0002902912,0.0002440956,0.0003641142,0.0001037772,0.0003049045,1.896401e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000832592,"about_ca_system_score_gemma":0.00001860101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003708776,"about_ca_topic_score_gemma":0.0001266694,"domain_scores_codex":[0.9981224,0.0007212888,0.0002833654,0.0005099183,0.0001362539,0.0002267679],"domain_scores_gemma":[0.999284,0.0002396747,0.0002300222,0.0001440628,0.00003583223,0.00006640864],"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":[0.0003338253,0.0002085406,0.07988551,0.00005581187,0.000005679673,0.000003193746,0.00008627379,0.0002755397,0.9106198,0.0001184167,1.332638e-7,0.008407278],"study_design_scores_gemma":[0.0004736562,0.0009233027,0.533438,0.000006980099,0.00001160878,0.00002692925,0.00003582671,0.3291268,0.1356439,0.0002081689,0.000001594673,0.0001032237],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977248,0.00004045066,0.001246348,0.0002612403,0.0002548378,0.0003787403,0.00001979024,0.00006913999,0.000004600044],"genre_scores_gemma":[0.9997763,0.00001583404,0.00004803255,0.00009285539,0.00001915472,0.00002867972,0.000004630598,0.00001362773,8.556275e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.774976,"threshold_uncertainty_score":0.5087873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03317774508776273,"score_gpt":0.2825559566020222,"score_spread":0.2493782115142594,"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."}}