{"id":"W2606351211","doi":"","title":"Fuzzy Weak Law of Large Numbers","year":2000,"lang":"en","type":"article","venue":"Joint International Conference on Information Sciences","topic":"Fuzzy Systems and Optimization","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Fuzzy logic; Computer science; Artificial intelligence; Law; Political science","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":[0.004986668,0.0007577622,0.0012174,0.002151873,0.00109098,0.004581132,0.0008172013,0.001607927,0.006220944],"category_scores_gemma":[0.02570823,0.0003886203,0.0006786456,0.001281953,0.005119854,0.006154016,0.00186152,0.004697309,0.0008150397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001911685,"about_ca_system_score_gemma":0.0009529355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001148237,"about_ca_topic_score_gemma":0.0007748499,"domain_scores_codex":[0.9983789,0.0005645519,0.0000682429,0.0002136716,0.0006523559,0.0001223905],"domain_scores_gemma":[0.9898015,0.006736274,0.0004608254,0.0007205618,0.001792896,0.0004878677],"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":[0.00001893406,0.000005978169,0.0000958473,0.00004423643,0.00001195906,0.00003350263,0.00006885777,0.001633639,0.0002836806,0.9915171,0.001700849,0.004585421],"study_design_scores_gemma":[0.00001617413,0.000009889742,0.0001495389,0.00001906552,0.00000689948,0.00003936399,0.00002389332,0.01696735,0.0001418409,0.9783128,0.004304412,0.000008579967],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04834557,0.01043849,0.8026686,0.02361943,0.002475654,0.00006060373,0.0002683723,0.0002783986,0.1118449],"genre_scores_gemma":[0.8652509,0.009328489,0.06910522,0.002875366,0.003776833,0.0003610498,0.0002308889,0.0001811359,0.04889013],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006220944,"threshold_uncertainty_score":0.02637237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08269369336862728,"score_gpt":0.3442849043372302,"score_spread":0.2615912109686029,"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."}}