{"id":"W3033182363","doi":"10.31124/advance.12401969.v1","title":"Logic, Probability Theory, and their Application to Legal Reasoning","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Probability and Statistical Research","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Correctness; Computer science; Probabilistic logic network; Probability theory; Subjective logic; Probabilistic argumentation; Philosophy of logic; Epistemic modal logic; Artificial intelligence; Applied probability; Theoretical computer science; Multimodal logic; Mathematics; Algorithm; Autoepistemic logic; Description logic; Probabilistic logic; Programming language","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002693804,0.0002559416,0.0004536688,0.00003657226,0.00009745427,0.0001098221,0.0004006963,0.0002399369,0.0001409256],"category_scores_gemma":[0.01408351,0.000181714,0.00007988387,0.0001067405,0.0001602137,0.00003886296,0.001659772,0.0007749695,0.00004765446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001098194,"about_ca_system_score_gemma":0.0001554378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008896401,"about_ca_topic_score_gemma":0.0001020762,"domain_scores_codex":[0.9977542,0.0004651082,0.0003706171,0.00083288,0.0002744797,0.0003026715],"domain_scores_gemma":[0.996056,0.002646159,0.00007091434,0.0007473327,0.0001658739,0.0003137678],"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":[0.0001312968,0.00008697953,0.00004781572,0.0008110917,0.00002722469,0.000001287158,0.000467515,0.000006284914,0.0001305768,0.984202,0.0004813157,0.01360665],"study_design_scores_gemma":[0.00007383203,0.00006838832,0.0003344109,0.00005150121,0.00001338926,0.000001882354,0.00008619032,0.003274195,0.0003430226,0.9945731,0.0009824996,0.0001975596],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01188519,0.00003704732,0.9611553,0.005017599,0.00003005403,0.002067317,0.00009680969,0.0002070955,0.01950358],"genre_scores_gemma":[0.7747403,0.00001014918,0.2236764,0.0004278467,0.00009052163,0.0005569661,0.00002936798,0.00002800294,0.0004403948],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7628551,"threshold_uncertainty_score":0.9942213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1095546330070194,"score_gpt":0.3895359150391862,"score_spread":0.2799812820321668,"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."}}