{"id":"W2014964943","doi":"10.1016/j.cogbrainres.2004.09.004","title":"A structural equation modeling analysis of attentional control: an event-related fMRI study","year":2004,"lang":"en","type":"article","venue":"Cognitive Brain Research","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"National Institute on Aging","keywords":"Psychology; Attentional control; Functional magnetic resonance imaging; Structural equation modeling; Cognitive psychology; Cognition; Prefrontal cortex; Task (project management); Attention network; Lateralization of brain function; Neuroscience; Developmental psychology; Artificial intelligence; Computer science; Mathematics; Statistics","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":[0.001031982,0.0001276822,0.0002816766,0.0006608953,0.000414558,0.00003610439,0.0002227666,0.00005811622,0.0001149909],"category_scores_gemma":[0.001226715,0.0001045776,0.000131227,0.001982336,0.0004245223,0.0002419705,0.00009426808,0.0003801326,0.00002683585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004470229,"about_ca_system_score_gemma":0.00004830572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001370491,"about_ca_topic_score_gemma":0.000132371,"domain_scores_codex":[0.9968522,0.0009817294,0.000351467,0.0006052144,0.0008427922,0.0003666422],"domain_scores_gemma":[0.9984018,0.0006546791,0.00007825469,0.000157341,0.0006223325,0.00008563713],"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":[0.001647584,0.003145648,0.1272946,0.00001574616,0.0009643435,0.0002263455,0.005529598,0.0362896,0.8159903,0.00166119,0.00002254256,0.007212509],"study_design_scores_gemma":[0.01603917,0.004919439,0.6778269,0.00008571641,0.001245189,0.00001627892,0.01523592,0.2376311,0.02741985,0.01893796,0.000001106396,0.0006413842],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971017,0.00002184264,0.0009493077,0.000921968,0.00006473387,0.0007139822,0.00007082309,0.00003114509,0.0001245241],"genre_scores_gemma":[0.9995972,0.000002603315,0.000006820086,0.0001450889,0.0000221546,0.00005610758,0.00002514271,0.00001000329,0.0001348841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7885704,"threshold_uncertainty_score":0.4264552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4622122238997799,"score_gpt":0.5277693880993414,"score_spread":0.06555716419956148,"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."}}