{"id":"W1588921741","doi":"10.1007/978-3-642-37453-1_2","title":"PUF-Tree: A Compact Tree Structure for Frequent Pattern Mining of Uncertain Data","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Tree (set theory); Computer science; Data mining; Tree structure; Uncertain data; K-ary tree; Algorithm; Mathematics; Binary tree","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":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0006206453,0.0005486108,0.0006941505,0.0005044788,0.0002258027,0.0005299749,0.008845815,0.000270455,0.00003252069],"category_scores_gemma":[0.0001075487,0.0004734515,0.0001123071,0.0004924236,0.000553131,0.000893076,0.002112183,0.0004636865,0.00001093487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001502722,"about_ca_system_score_gemma":0.0005327724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002104723,"about_ca_topic_score_gemma":0.0003810288,"domain_scores_codex":[0.9958405,0.00002506484,0.000717648,0.001944619,0.0008165932,0.0006555207],"domain_scores_gemma":[0.9943343,0.000734627,0.0005730249,0.003863272,0.0003038438,0.0001909394],"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":[0.000001618936,0.00002518395,0.00005425159,0.00005847182,0.00002127611,0.000006486645,0.0003827537,0.001955097,0.000210597,0.00294915,0.0007699376,0.9935652],"study_design_scores_gemma":[0.0003461364,0.0001735894,0.0002821773,0.000409316,0.00002014569,0.00003525572,7.562267e-7,0.9587175,0.0007031994,0.03425682,0.004462501,0.0005925881],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001428893,0.0002898962,0.9956691,0.001097297,0.0007479971,0.0007527011,0.0006753164,0.00008892584,0.0005358246],"genre_scores_gemma":[0.05758907,0.00001999986,0.9405329,0.0007306458,0.0004783792,0.00001965912,0.0003633974,0.00004736592,0.0002185947],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9929726,"threshold_uncertainty_score":0.9997717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04921570632610776,"score_gpt":0.2919843086638553,"score_spread":0.2427686023377476,"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."}}