{"id":"W2140848254","doi":"10.1109/nafips.2004.1336250","title":"On the implication problem in granular knowledge systems","year":2004,"lang":"en","type":"article","venue":"IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04.","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Probabilistic logic; Computer science; Representation (politics); Bayesian network; Set (abstract data type); Theoretical computer science; Knowledge representation and reasoning; Markov chain; Markov process; Logical conjunction; Bayesian probability; Artificial intelligence; Mathematics; Machine learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007922913,0.0004970708,0.001032678,0.001383743,0.001980209,0.003695129,0.001519916,0.002693398,0.00444172],"category_scores_gemma":[0.02851455,0.0005399266,0.001099819,0.002363699,0.004468109,0.009826812,0.003518032,0.004030203,0.0003463426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002114568,"about_ca_system_score_gemma":0.001051892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002926416,"about_ca_topic_score_gemma":0.001742807,"domain_scores_codex":[0.9950046,0.002394769,0.0004098169,0.0006231676,0.001236794,0.0003308443],"domain_scores_gemma":[0.9763984,0.02102567,0.0007563078,0.0007416724,0.0007877891,0.0002900948],"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":[0.00008752904,0.00002811716,0.0005056769,0.0001411943,0.00002831721,0.0004642029,0.0003751807,0.04556816,0.0003227261,0.9249594,0.001558587,0.02596097],"study_design_scores_gemma":[0.000009259871,0.000005330434,0.00006595684,0.00001772562,0.000006274368,0.00004674632,0.00004207435,0.04908754,0.00009547141,0.9498112,0.0008065921,0.000005885315],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0596782,0.002469462,0.9008605,0.00877442,0.0002193039,0.00008232905,0.0002358791,0.0001982293,0.02748167],"genre_scores_gemma":[0.8053495,0.002161565,0.1861382,0.001009595,0.0005656749,0.0001554879,0.0003419933,0.00006968461,0.004208333],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007922913,"threshold_uncertainty_score":0.04190087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01518826327479748,"score_gpt":0.2480130725456955,"score_spread":0.232824809270898,"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."}}