{"id":"W1705572361","doi":"10.22329/il.v24i1.2132","title":"Bayesian Informal Logic and Fallacy","year":2004,"lang":"en","type":"article","venue":"Informal Logic","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"London School of Economics and Political Science","keywords":"Fallacy; Inductive reasoning; Variety (cybernetics); Inference; Computer science; Bayesian inference; Bayesian probability; Epistemology; Statistical inference; Artificial intelligence; Deductive reasoning; Bayesian network; Causal inference; Machine learning; Bayesian statistics; Frequentist inference; Mathematics; Philosophy; Econometrics; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01294412,0.0008917553,0.001276996,0.004882595,0.004026362,0.006936966,0.001976557,0.00407654,0.006757857],"category_scores_gemma":[0.03564003,0.0006908884,0.00138164,0.00311606,0.01922436,0.01377558,0.004481355,0.00638596,0.001126691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005406992,"about_ca_system_score_gemma":0.002761311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003069689,"about_ca_topic_score_gemma":0.001781668,"domain_scores_codex":[0.9870936,0.007038412,0.0007691701,0.001461183,0.002973653,0.0006639114],"domain_scores_gemma":[0.9742561,0.02003306,0.001657761,0.00151199,0.001965918,0.0005751688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000003806503,0.000004173512,0.00006356328,0.00002355211,0.000004202404,0.00002860645,0.000178956,0.0003058425,0.0000223384,0.9962558,0.0007024785,0.002406638],"study_design_scores_gemma":[0.000002460999,9.090306e-7,0.00001751615,0.00001254867,0.000001554042,0.00001163943,0.00001594759,0.0004835075,0.00001034383,0.9978458,0.001595814,0.000001897465],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0319935,0.01284428,0.716218,0.05485366,0.0008830975,0.0001876089,0.0005296683,0.0007061446,0.181784],"genre_scores_gemma":[0.801852,0.006523453,0.1658124,0.008272458,0.001814591,0.0005959428,0.0006150765,0.0002549619,0.01425919],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01294412,"threshold_uncertainty_score":0.06845587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02421553473010509,"score_gpt":0.2506493351318307,"score_spread":0.2264338004017256,"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."}}