{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001514401,0.00004297117,0.00005450232,0.0000526859,0.00007330791,0.0001137156,0.0003616191,0.00002636093,0.00002067593],"category_scores_gemma":[0.00003093941,0.00004072436,0.00001254196,0.0002048934,0.00004140728,0.002079704,0.00007657719,0.00002689093,0.0003548958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001152099,"about_ca_system_score_gemma":0.00002386592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006486711,"about_ca_topic_score_gemma":0.00001789711,"domain_scores_codex":[0.9994158,0.000009057287,0.0002930005,0.00008031583,0.000134715,0.00006718325],"domain_scores_gemma":[0.9991862,0.00002366476,0.0001930404,0.0004165056,0.0001564565,0.00002416733],"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":[0.000004736349,0.00003635474,0.00078078,0.00001228148,0.00001022272,5.165203e-8,0.004127428,0.000008493441,0.002186311,0.03134197,0.006994259,0.9544971],"study_design_scores_gemma":[0.0003267814,0.00005053619,0.1688576,0.00002170002,0.000009186651,0.000001747232,0.0001486955,0.6823884,0.1067311,0.01147282,0.02981299,0.0001783851],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1321618,0.000004475367,0.86638,0.0002006899,0.0001797624,0.00007439905,0.0002087652,0.00006116901,0.0007288984],"genre_scores_gemma":[0.97985,0.000002342855,0.01968621,0.00005938752,0.0000406786,0.00001062238,0.0003350187,0.000001041345,0.00001470957],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9543187,"threshold_uncertainty_score":0.4561586,"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."}}