{"id":"W2401505247","doi":"","title":"Solving Valid Syllogistic Problems using a Bidirectional Heteroassociative Memory","year":2014,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Syllogism; Deductive reasoning; Connectionism; Representation (politics); Cognitive science; Computer science; Simple (philosophy); Artificial intelligence; Psychology; Epistemology; Cognitive psychology; Artificial neural network; Philosophy; Law","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005524454,0.0002883928,0.0002779135,0.0002595734,0.0004338348,0.002758072,0.0009951659,0.0001054225,0.00006120224],"category_scores_gemma":[0.0008637232,0.0002700975,0.0001830317,0.0009441882,0.0001391861,0.008165346,0.0007450436,0.000367903,0.0006996458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008349437,"about_ca_system_score_gemma":0.0001654578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005541117,"about_ca_topic_score_gemma":0.000001027307,"domain_scores_codex":[0.9974555,0.0001804613,0.0003941457,0.0007378174,0.000580824,0.0006512614],"domain_scores_gemma":[0.9986199,0.0004016377,0.0002170478,0.0003813626,0.0001029228,0.0002771339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001062581,0.001775954,0.3764787,0.0005615497,0.0005630665,0.0002082234,0.002078927,0.002818226,0.02246339,0.1064362,0.005158921,0.4813505],"study_design_scores_gemma":[0.003278458,0.0007995373,0.03185777,0.001515085,0.00009747024,0.0002936532,0.0002566214,0.3533313,0.01711069,0.3460089,0.240591,0.004859511],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.214099,0.0001776076,0.6926738,0.00129584,0.001084734,0.0004728634,0.0003824133,0.001699309,0.08811439],"genre_scores_gemma":[0.9874534,0.000003745087,0.01040353,0.00101456,0.0002212158,0.00001873945,0.00004277549,0.00003206305,0.0008099905],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7733544,"threshold_uncertainty_score":0.9999751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03298692545476894,"score_gpt":0.2381447738560439,"score_spread":0.2051578484012749,"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."}}