{"id":"W2089487740","doi":"10.1016/j.neulet.2006.09.073","title":"Spatiotemporal analysis of feedback processing during a card sorting task using spatially filtered MEG","year":2006,"lang":"en","type":"article","venue":"Neuroscience Letters","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children; SickKids Foundation","funders":"","keywords":"Magnetoencephalography; Anterior cingulate cortex; Neural correlates of consciousness; Stimulus (psychology); Psychology; Neuroscience; Computer science; Event-related potential; Functional magnetic resonance imaging; Card sorting; Artificial intelligence; Pattern recognition (psychology); Electroencephalography; Task (project management); Cognitive psychology; Cognition","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":[0.0001334015,0.0002530224,0.0004263581,0.0004685277,0.0005187943,0.0001057106,0.0004552174,0.00004808231,0.00000621724],"category_scores_gemma":[0.0001232495,0.0002251433,0.0002068107,0.002448059,0.0006985652,0.0004818942,0.000149875,0.0002060386,0.000002122389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004291241,"about_ca_system_score_gemma":0.00002655154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004256588,"about_ca_topic_score_gemma":0.00005811675,"domain_scores_codex":[0.997251,0.0001228702,0.0005701992,0.0009069975,0.0005805485,0.0005683563],"domain_scores_gemma":[0.9990429,0.00004723034,0.0004990014,0.0003033074,0.00004380933,0.00006379823],"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":[0.00001765903,0.00006854064,0.08682192,0.00001592239,0.000002934205,0.00006149813,0.00009591541,0.005864766,0.9067592,0.000003194306,0.00002579373,0.0002626724],"study_design_scores_gemma":[0.0002707737,0.0000498882,0.2708335,0.00002375609,0.0001968123,0.00002288314,0.00001737544,0.006532297,0.7217448,0.00001142086,0.00002611983,0.0002703676],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976231,0.000009222034,0.0004725679,0.001156496,0.0003634067,0.000177683,0.00002439054,0.00008711251,0.00008600321],"genre_scores_gemma":[0.9976408,0.000001958135,0.000253137,0.001946047,0.00007508596,0.000006278055,0.000002001425,0.00001802655,0.00005663994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1850143,"threshold_uncertainty_score":0.9181077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1007972876692099,"score_gpt":0.3396291733613745,"score_spread":0.2388318856921647,"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."}}