{"id":"W2153498547","doi":"10.1109/isuma.1995.527689","title":"Geometric compatibility modification in FuzzyCLIPS","year":2002,"lang":"en","type":"article","venue":"","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Compatibility (geochemistry); Inference; Computer science; Rule of inference; Fuzzy inference; Fuzzy set; Fuzzy logic; Data mining; Adaptive neuro fuzzy inference system; Artificial intelligence; Mathematics; Fuzzy control system; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003130976,0.000444381,0.000549486,0.001400733,0.001128563,0.001953859,0.001425223,0.0009379708,0.004160147],"category_scores_gemma":[0.008667132,0.000481158,0.001136483,0.001124204,0.003054671,0.005482841,0.002162208,0.001403378,0.0008452499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001135293,"about_ca_system_score_gemma":0.001034584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001370613,"about_ca_topic_score_gemma":0.0009325476,"domain_scores_codex":[0.9947925,0.0009276549,0.0003897177,0.001048841,0.002644106,0.0001972014],"domain_scores_gemma":[0.9968149,0.001101189,0.0002979006,0.0008096255,0.0008924331,0.00008398025],"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":[0.0001050429,0.00004974634,0.0009867175,0.0001502486,0.00004318832,0.0002722982,0.0008064082,0.01711462,0.01148617,0.7641729,0.001464963,0.2033478],"study_design_scores_gemma":[0.00004297754,0.0002115227,0.001242676,0.0000456958,0.00006873124,0.0006266175,0.0001835047,0.1540342,0.04073486,0.7682838,0.03444937,0.0000759272],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02618544,0.0001558453,0.9527286,0.0001736551,0.0000539646,0.0001379825,0.00005324543,0.0007929131,0.01971824],"genre_scores_gemma":[0.4350616,0.0002077751,0.5551593,0.0002584,0.0001056717,0.0001772414,0.0002013866,0.0001922306,0.008636347],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004160147,"threshold_uncertainty_score":0.01655835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0563760513235637,"score_gpt":0.2360980924018506,"score_spread":0.1797220410782869,"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."}}