{"id":"W2803257473","doi":"10.1016/j.pbiomolbio.2018.05.010","title":"Syntax meets semantics during brain logical computations","year":2018,"lang":"en","type":"review","venue":"Progress in Biophysics and Molecular Biology","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Syntax; Computer science; Semantics (computer science); Semantic memory; Comprehension; Cognitive science; Cognition; Artificial intelligence; Natural language processing; Programming language; Psychology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001021596,0.0003376633,0.0007357958,0.0001626867,0.0001246821,0.0000646511,0.0002468225,0.000304539,0.000002525231],"category_scores_gemma":[0.00009009714,0.0002638892,0.0001734001,0.0003736529,0.0005172484,0.00003133188,0.000304353,0.0002925838,0.00001518613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002945266,"about_ca_system_score_gemma":0.00003520467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001756714,"about_ca_topic_score_gemma":0.000001057913,"domain_scores_codex":[0.99808,0.0003204411,0.0003739149,0.0007745007,0.00009441479,0.0003566869],"domain_scores_gemma":[0.9992585,0.0001767835,0.0002273572,0.0002405785,0.00002668837,0.00007014482],"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":[0.00001598677,0.0002824648,0.00004764532,0.005161071,0.00005568844,0.0003589636,0.00003051544,0.000001678343,0.0101927,0.0970346,0.00002449363,0.8867942],"study_design_scores_gemma":[0.001173655,0.001182812,0.00007746767,0.007195892,0.0004208062,0.0007223398,0.000007580413,0.002259146,0.004559481,0.03439233,0.9454228,0.002585667],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01162068,0.9858821,0.0005251191,0.0004269114,0.0005177436,0.0007969815,0.00008555682,0.00006654062,0.00007838423],"genre_scores_gemma":[0.02071648,0.9782467,0.0004000909,0.0002470512,0.0001394242,0.00009870169,0.00008717641,0.0000443476,0.0000200685],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9453983,"threshold_uncertainty_score":0.9999813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04075946750360177,"score_gpt":0.3522262556798439,"score_spread":0.3114667881762422,"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."}}