{"id":"W4399895001","doi":"10.18280/ria.380317","title":"MeAR-CP: Evaluation of the Quality of Association Rules Using Constraint Programming","year":2024,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Constraint programming; Association (psychology); Constraint (computer-aided design); Computer science; Association rule learning; Quality (philosophy); Programming language; Mathematics; Artificial intelligence; Psychology; Statistics; Stochastic programming; Philosophy; Epistemology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.01179138,0.001841243,0.001915061,0.007168006,0.0007895484,0.00290095,0.003005086,0.001716633,0.002832179],"category_scores_gemma":[0.04804979,0.0003463593,0.001931207,0.008565836,0.0009579724,0.002498522,0.001523133,0.001648935,0.0004849115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001394627,"about_ca_system_score_gemma":0.003231646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01012587,"about_ca_topic_score_gemma":0.01171963,"domain_scores_codex":[0.9855112,0.00501212,0.001986265,0.001755636,0.00529854,0.0004362475],"domain_scores_gemma":[0.9328877,0.05405002,0.00377122,0.003040052,0.005472731,0.0007783844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001649619,0.00105866,0.03942298,0.003256433,0.001714785,0.0006100134,0.0003859646,0.380979,0.008850374,0.0120036,0.02164283,0.5284257],"study_design_scores_gemma":[0.0001212273,0.0004546712,0.007256454,0.0001411295,0.0001278008,0.0004426448,0.000307844,0.9668415,0.01057958,0.008094569,0.005562804,0.000069769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3087314,0.00415127,0.6464657,0.001906029,0.0003368229,0.001258156,0.01745294,0.007885168,0.01181256],"genre_scores_gemma":[0.3373804,0.000730857,0.6469394,0.0002541256,0.00007624807,0.0005918866,0.01236458,0.0003438225,0.00131857],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01179138,"threshold_uncertainty_score":0.06235951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1154704532977992,"score_gpt":0.3601265626909797,"score_spread":0.2446561093931806,"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."}}