{"id":"W2077981172","doi":"10.1109/bdcloud.2014.136","title":"A Data Science Solution for Mining Interesting Patterns from Uncertain Big Data","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Big data; Computer science; Uncertain data; Database transaction; Data mining; Transaction data; Focus (optics); Computation; Tree (set theory); Data science; Data stream mining; Database; Algorithm; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001730861,0.0008403222,0.0009854912,0.002347041,0.001246177,0.002084172,0.002073905,0.001462455,0.001955133],"category_scores_gemma":[0.008297678,0.0006524962,0.002102299,0.003876022,0.0009463956,0.00359094,0.002428884,0.001943062,0.0007834958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005861424,"about_ca_system_score_gemma":0.002021111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002302467,"about_ca_topic_score_gemma":0.003196519,"domain_scores_codex":[0.9984352,0.0002311384,0.0001506067,0.0003741053,0.0007259417,0.00008302869],"domain_scores_gemma":[0.9976965,0.001128,0.0002339841,0.0003816836,0.0004354561,0.0001245132],"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":[0.000440115,0.0005434513,0.005854717,0.001408322,0.0004714613,0.001259909,0.00097638,0.209248,0.01170915,0.1757962,0.02717092,0.5651214],"study_design_scores_gemma":[0.00005601166,0.00007836946,0.0004576085,0.00005295208,0.00005266813,0.000414614,0.0002496007,0.7878079,0.003486618,0.1953614,0.01195303,0.00002926672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005142654,0.0002462773,0.9916874,0.0009703551,0.00005976747,0.0001313235,0.0003865053,0.0005212582,0.000854466],"genre_scores_gemma":[0.06141617,0.0003159968,0.9360602,0.000266371,0.00009546187,0.0002257843,0.000772836,0.0000498342,0.0007973077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002347041,"threshold_uncertainty_score":0.009153783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2674852335436116,"score_gpt":0.3601249488761387,"score_spread":0.09263971533252707,"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."}}