{"id":"W4328050389","doi":"10.1093/cercor/bhad080","title":"Elucidating medial temporal and frontal lobe contributions to approach-avoidance conflict decision-making using functional MRI and the hierarchical drift diffusion model","year":2023,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Memory and Neural Mechanisms","field":"Neuroscience","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Canadian Institutes of Health Research; Government of Canada","keywords":"Perirhinal cortex; Psychology; Prefrontal cortex; Temporal lobe; Neuroscience; Cognitive psychology; Dorsolateral prefrontal cortex; Ventromedial prefrontal cortex; Anterior cingulate cortex; Frontal lobe; Functional magnetic resonance imaging; Cognition","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005822748,0.0002245876,0.0002944515,0.0001178576,0.00109654,0.0001518829,0.0002083613,0.0001051999,0.00003272621],"category_scores_gemma":[0.00135409,0.0001595375,0.00007185173,0.0003778474,0.0003364082,0.0002495036,0.0004622624,0.0004027241,0.00001731981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003736299,"about_ca_system_score_gemma":0.00006336243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008403933,"about_ca_topic_score_gemma":0.00001147518,"domain_scores_codex":[0.9978332,0.0002504693,0.0003404929,0.0006764097,0.0004702591,0.0004291628],"domain_scores_gemma":[0.9983628,0.001030483,0.0001089575,0.0002367678,0.00004309146,0.0002179304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001250726,0.00007087897,0.0007443104,0.00002742228,0.00001083569,0.00004609327,0.001374419,0.003437308,0.9413934,0.04541555,0.000412468,0.005816635],"study_design_scores_gemma":[0.001944429,0.00007891555,0.003307335,0.00007546381,0.00002464163,0.0001595535,0.0001700088,0.9545664,0.02276209,0.01657632,0.000056459,0.0002784205],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8197609,0.00002315691,0.1784899,0.000484495,0.0003902418,0.0004859394,0.00009052511,0.0001041025,0.0001707334],"genre_scores_gemma":[0.9954501,0.00001568802,0.003006188,0.001108456,0.0002338336,0.00003339954,0.00001369743,0.00002280239,0.0001158181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9511291,"threshold_uncertainty_score":0.843381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06394616021433401,"score_gpt":0.3236749155022352,"score_spread":0.2597287552879012,"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."}}