{"id":"W4221114631","doi":"10.1111/cogs.13116","title":"The Neural Correlates of Analogy Component Processes","year":2022,"lang":"en","type":"review","venue":"Cognitive Science","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Queen's University","funders":"","keywords":"Analogy; Cognitive science; Computer science; Inference; Computational model; Schema (genetic algorithms); Cognition; Cognitive architecture; Cognitive neuroscience; Computational neuroscience; Deductive reasoning; Context (archaeology); Artificial intelligence; Psychology; Neuroscience; Machine learning","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":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0004372193,0.0002928256,0.000713951,0.0001856783,0.001561871,0.00006034044,0.001385241,0.00004758938,0.00007396934],"category_scores_gemma":[0.002632063,0.0001615732,0.0001793003,0.002518697,0.006418711,0.0001541423,0.000760921,0.0005237637,0.00004397064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003928957,"about_ca_system_score_gemma":0.0003404659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003633591,"about_ca_topic_score_gemma":0.000003395481,"domain_scores_codex":[0.9973516,0.0003003977,0.0004534039,0.0008327746,0.0005867394,0.0004750997],"domain_scores_gemma":[0.9960254,0.00299133,0.0005099442,0.0002403252,0.0001612269,0.00007179328],"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":[0.00000997968,0.00009141616,0.00004635821,0.0006385223,0.000005765298,0.00003815587,0.0000755913,1.111387e-7,0.0002088875,0.00009370482,0.00006007781,0.9987314],"study_design_scores_gemma":[0.0002081994,0.0005769231,0.0001832559,0.00172452,0.0004776002,0.000405763,0.0003801988,0.000006367304,0.001914097,0.0002859671,0.9932537,0.0005833968],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002833555,0.9932374,0.000001503866,0.0000509446,0.00130734,0.0006771354,0.0001108977,0.00003772437,0.001743489],"genre_scores_gemma":[0.02156987,0.9778478,0.000001210069,0.0001174185,0.00002886946,0.000155941,0.000003757344,0.00001366392,0.0002615114],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.998148,"threshold_uncertainty_score":0.999738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3645191564033181,"score_gpt":0.4644513340802704,"score_spread":0.09993217767695234,"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."}}