{"id":"W2801771958","doi":"10.3390/info9050119","title":"Fast Identification of High Utility Itemsets from Candidates","year":2018,"lang":"en","type":"article","venue":"Information","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Science Foundation of Hubei Province","keywords":"Computation; Computer science; Identification (biology); Data mining; Tree (set theory); Set (abstract data type); Algorithm; Mathematics","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":[0.001999427,0.001098054,0.001925473,0.004819131,0.00135081,0.002045938,0.001987513,0.00102479,0.001949794],"category_scores_gemma":[0.01281212,0.0006244598,0.001472948,0.005422716,0.0005078541,0.003337738,0.002033689,0.001168276,0.001354576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006650212,"about_ca_system_score_gemma":0.002367133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001572309,"about_ca_topic_score_gemma":0.002724878,"domain_scores_codex":[0.9981313,0.0002637808,0.0001892484,0.0003215364,0.0008431774,0.0002509055],"domain_scores_gemma":[0.9947221,0.002510687,0.0005629666,0.0006821664,0.001242463,0.0002795045],"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":[0.001123935,0.0005266097,0.02261315,0.0007598154,0.0001984812,0.001138819,0.0008055281,0.04797343,0.01621974,0.02384308,0.01725694,0.8675405],"study_design_scores_gemma":[0.0001451228,0.000489948,0.007103046,0.000163893,0.0001389994,0.001811253,0.000776721,0.892689,0.02461349,0.05934601,0.01263497,0.00008760372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1047847,0.001015715,0.8868128,0.0004106724,0.00009129148,0.0008404357,0.001514314,0.002332208,0.002197857],"genre_scores_gemma":[0.3844779,0.0005789966,0.6059856,0.0001575147,0.00008280999,0.0005337916,0.00542419,0.0001895903,0.002569506],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004819131,"threshold_uncertainty_score":0.0105741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00928728821890769,"score_gpt":0.2380634091808697,"score_spread":0.228776120961962,"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."}}