{"id":"W2913918884","doi":"10.1109/bigdata.2018.8622138","title":"Candidate List Maintenance in High Utility Sequential Pattern Mining","year":2018,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research and Productivity Council; National Research Council Canada","funders":"","keywords":"Concatenation (mathematics); Computer science; Set (abstract data type); Data mining; Tree (set theory); Exploit; Descendant; Sequential Pattern Mining; Artificial intelligence; Mathematics; Arithmetic","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007242964,0.001066156,0.001946101,0.00532952,0.001746635,0.002767152,0.003647412,0.001480621,0.002952871],"category_scores_gemma":[0.03841312,0.0008869345,0.001368597,0.005499335,0.001106714,0.005464007,0.002417188,0.001789017,0.00140616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001021177,"about_ca_system_score_gemma":0.003080138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002273535,"about_ca_topic_score_gemma":0.004543385,"domain_scores_codex":[0.9935557,0.00226135,0.0006428059,0.0009789605,0.002122895,0.0004382705],"domain_scores_gemma":[0.9712554,0.01918537,0.001909577,0.003914683,0.003113695,0.0006212536],"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":[0.002046712,0.0008363418,0.02809115,0.001049601,0.0003107481,0.001347897,0.0009063559,0.1460497,0.01106928,0.03594952,0.01269187,0.7596509],"study_design_scores_gemma":[0.0001313361,0.0006570502,0.002554817,0.0001243189,0.0001174489,0.000851799,0.0003127554,0.9166511,0.01104602,0.06061469,0.006886691,0.00005194734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08465409,0.001370166,0.9068652,0.0004464676,0.00007729763,0.000507931,0.001240562,0.002791118,0.002047037],"genre_scores_gemma":[0.4529078,0.0005028312,0.5390874,0.0002540642,0.0001081574,0.0005108599,0.003932035,0.0002711386,0.00242583],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007242964,"threshold_uncertainty_score":0.03830492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02066389643000175,"score_gpt":0.26834608569359,"score_spread":0.2476821892635883,"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."}}