{"id":"W2465555842","doi":"10.1080/18756891.2016.1204111","title":"An Interpretable Logical Theory: The case of Compensatory Fuzzy Logic","year":2016,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence Systems","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Interpretability; Fuzzy logic; Non-classical logic; Logical consequence; Natural language; Computer science; Logical connective; Logical framework; Mathematics; Natural deduction; Artificial intelligence; Natural (archaeology); 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":[],"consensus_categories":[],"category_scores_codex":[0.01065726,0.0002198971,0.0005302734,0.0006811666,0.0001194284,0.0004681518,0.003184894,0.0001100451,0.0007850777],"category_scores_gemma":[0.004924163,0.0001023631,0.0003267669,0.0003845098,0.0004746549,0.0009537788,0.0002297304,0.0002565825,0.0001753548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001525943,"about_ca_system_score_gemma":0.0002370911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003559256,"about_ca_topic_score_gemma":0.000007323168,"domain_scores_codex":[0.9921335,0.001516869,0.002728444,0.0003651201,0.003034542,0.0002215409],"domain_scores_gemma":[0.9794885,0.01078947,0.002232968,0.0004688222,0.006843661,0.0001766078],"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":[0.0006289015,0.0002911218,0.001543176,0.000005311257,0.0002599951,0.001541244,0.00117545,0.238114,0.001787716,0.5971909,0.001101096,0.1563611],"study_design_scores_gemma":[0.0004905967,0.0004100647,0.001913463,0.0003666745,0.00002706415,0.01765885,0.005126697,0.08983365,0.0006451642,0.8808202,0.002449349,0.0002582231],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1875012,0.0003178771,0.8065129,0.0008797296,0.003845759,0.0001565971,0.00005702427,0.00001289723,0.0007160616],"genre_scores_gemma":[0.9947779,0.00001243095,0.004255287,0.0002546165,0.0005263368,0.000004139674,0.000001497081,0.00001445521,0.0001534065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8072767,"threshold_uncertainty_score":0.8596051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1648336511681643,"score_gpt":0.4599324850344296,"score_spread":0.2950988338662652,"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."}}