{"id":"W1990984688","doi":"10.1007/bf02945466","title":"Analyzing and mining ordered information tables","year":2003,"lang":"en","type":"article","venue":"Journal of Computer Science and Technology","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Ranking (information retrieval); Table (database); Dependency (UML); Association rule learning; Data mining; Value (mathematics); Order (exchange); Information extraction; Theory of computation; Theoretical computer science; Information retrieval; Artificial intelligence; Machine learning; Algorithm","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":[0.0009062758,0.00006966298,0.0001475592,0.000780873,0.0002036415,0.0003184907,0.0005091938,0.00005066459,8.330272e-7],"category_scores_gemma":[0.0001195987,0.00005158105,0.00001269312,0.00132812,0.0002846509,0.001996075,0.0001948842,0.0001147481,7.684741e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001635734,"about_ca_system_score_gemma":0.0001549777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001067279,"about_ca_topic_score_gemma":5.084265e-7,"domain_scores_codex":[0.999203,0.00001488604,0.0002596035,0.0001180489,0.0002108033,0.000193605],"domain_scores_gemma":[0.999175,0.00003232045,0.0002196876,0.0001543737,0.0003507709,0.00006781713],"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":[0.000001494916,0.00001698765,0.006144414,0.00000790631,0.000009268854,0.00001790366,0.0004978709,0.00006837842,0.0003365689,0.1355278,0.0002605758,0.8571108],"study_design_scores_gemma":[0.004251612,0.004156058,0.02472525,0.0003305391,0.00005345499,0.01589955,0.001281022,0.5809732,0.008232591,0.2326841,0.126079,0.001333677],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2708564,0.0004713537,0.7261497,0.001837826,0.0002762237,0.00003309134,1.100976e-7,0.00002740516,0.0003479471],"genre_scores_gemma":[0.6938549,0.00009045882,0.305886,0.0001530296,0.00001345247,2.80691e-7,2.399959e-8,8.359349e-7,9.620791e-7],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8557771,"threshold_uncertainty_score":0.3071213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00813276642335179,"score_gpt":0.2177216585948505,"score_spread":0.2095888921714987,"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."}}