{"id":"W1576216411","doi":"10.22329/il.v25i1.1040","title":"The Logic of Deep Disagreements","year":2005,"lang":"en","type":"article","venue":"Informal Logic","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":191,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Epistemology; Computer science; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002672328,0.00008542189,0.00008559402,0.00002612405,0.0001415948,0.00008369483,0.0009429583,0.00004213375,0.00001829623],"category_scores_gemma":[0.00003060704,0.00005035125,0.00003993489,0.0001465531,0.00007182421,0.0004618273,0.0002253804,0.0001003135,0.0001818624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001227759,"about_ca_system_score_gemma":0.00002564294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007993341,"about_ca_topic_score_gemma":0.00001234346,"domain_scores_codex":[0.99915,0.00001705673,0.0002627572,0.0001049948,0.0002128499,0.0002523655],"domain_scores_gemma":[0.999367,0.00005658111,0.00009852892,0.0003610901,0.00006503446,0.00005174472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005772004,0.00002784942,0.0002594954,0.000005032276,0.000008750137,0.000001168681,0.0003667933,0.002578771,0.0000761322,0.5883914,0.0002523924,0.4080265],"study_design_scores_gemma":[0.0005674844,0.0005330196,0.008057526,0.0000247199,0.000009974502,0.00003504147,0.000108499,0.8680259,0.002190863,0.08666319,0.03334443,0.0004393747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006503168,0.0002363277,0.9444803,0.001576014,0.0001744195,0.00008046863,8.633366e-7,0.00008361571,0.04686481],"genre_scores_gemma":[0.9798515,0.00003309769,0.01884395,0.0009730004,0.00005445219,0.000005800429,8.030162e-7,0.000001804166,0.0002355783],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9733483,"threshold_uncertainty_score":0.2337534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02678810802545237,"score_gpt":0.2643453754008185,"score_spread":0.2375572673753661,"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."}}