{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008676829,0.0001867516,0.0002290511,0.0008326676,0.0002249923,0.001367154,0.0004800926,0.0005886688,0.003609647],"category_scores_gemma":[0.0109448,0.0002024695,0.0002274759,0.0008171012,0.0008883813,0.001399838,0.0007085446,0.0008852708,0.0003765612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002948944,"about_ca_system_score_gemma":0.0002786756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008774725,"about_ca_topic_score_gemma":0.0008705432,"domain_scores_codex":[0.9996821,0.00008302557,0.0000233372,0.0001003552,0.00008175545,0.00002947174],"domain_scores_gemma":[0.9974981,0.001467046,0.0005009752,0.0002317592,0.0002007306,0.0001014159],"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":[0.001358326,0.000547875,0.2299692,0.001162198,0.0008140054,0.001382992,0.002634389,0.01068387,0.07451132,0.1394659,0.004860435,0.5326095],"study_design_scores_gemma":[0.00006636734,0.0002599847,0.822117,0.0001129163,0.0001925457,0.002342333,0.0004361109,0.009095557,0.003753864,0.155605,0.005962433,0.00005587614],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.9122217,0.01179951,0.03185776,0.002411413,0.0001538297,0.0001436295,0.0007540286,0.0001362334,0.04052182],"genre_scores_gemma":[0.9890289,0.003595038,0.005469288,0.00016857,0.00009687335,0.00006237375,0.0003167791,0.00002194217,0.001240218],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.003609647,"threshold_uncertainty_score":0.01207548,"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."}}