{"id":"W1530348080","doi":"10.1109/nafips.2001.944678","title":"Linguistic association rules","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Association rule learning; Computer science; ENCODE; Association (psychology); Class (philosophy); Apriori algorithm; A priori and a posteriori; Database transaction; Hypercube; Fuzzy logic; Artificial intelligence; Data mining; Natural language processing; Theoretical computer science; Information retrieval; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007216755,0.00002859103,0.00003123451,0.0000175736,0.00005908962,0.0001022539,0.0002672579,0.00001587891,0.00009769021],"category_scores_gemma":[0.00008794314,0.00002557046,0.00001217248,0.00009994256,0.000002941966,0.00009420177,0.00005112722,0.00002941235,0.001317738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002243864,"about_ca_system_score_gemma":0.00000261925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001326181,"about_ca_topic_score_gemma":0.000001249288,"domain_scores_codex":[0.9996493,0.000005652873,0.00005997967,0.0001099919,0.00009054996,0.0000845488],"domain_scores_gemma":[0.999661,0.00004940659,0.00002651529,0.0002046147,0.00003272007,0.00002573365],"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":[3.392969e-8,0.00006684133,0.0004401101,0.000001528723,0.000007442806,0.000001487967,0.0005200835,0.00000259214,0.00004276565,0.622834,0.05980197,0.3162811],"study_design_scores_gemma":[0.00006370794,0.000009660678,0.001598013,0.000002166438,0.00000200147,0.000001544226,0.000002974927,0.6869198,0.0001156011,0.004235733,0.3069694,0.00007937885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000619184,0.00004443623,0.7631595,0.002313999,0.0001643406,0.00003611563,0.000004844187,0.0002696246,0.233388],"genre_scores_gemma":[0.1699037,0.00003091224,0.7938112,0.0007653389,0.0002275387,0.00002059364,0.000007689156,0.000005212416,0.03522779],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6869172,"threshold_uncertainty_score":0.9994599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02069156690568929,"score_gpt":0.2343969811271816,"score_spread":0.2137054142214923,"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."}}