{"id":"W2395766643","doi":"10.1007/978-3-319-13186-3_70","title":"BigSAM: Mining Interesting Patterns from Probabilistic Databases of Uncertain Big Data","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Big data; Uncertain data; Probabilistic logic; Database transaction; Data mining; Process (computing); Database; Artificial intelligence","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":["open_science"],"category_scores_codex":[0.001339163,0.0005447683,0.0006649006,0.000728359,0.0001512624,0.000572023,0.01080256,0.0001229432,0.0000211414],"category_scores_gemma":[0.0005463839,0.0004882228,0.00007090771,0.0004622826,0.0005467918,0.0009572013,0.01177095,0.0004836945,0.00001748792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009877768,"about_ca_system_score_gemma":0.0003005932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004265238,"about_ca_topic_score_gemma":0.000561407,"domain_scores_codex":[0.9951684,0.00006221228,0.0007792024,0.002363897,0.001025426,0.0006008164],"domain_scores_gemma":[0.9929579,0.001352119,0.0005927787,0.004801978,0.0001574138,0.0001377704],"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":[0.000002925541,0.0000232409,0.0003125448,0.0001158208,0.0000204158,0.00006161753,0.000227135,0.002868115,0.00003364061,0.00451931,0.0000901896,0.991725],"study_design_scores_gemma":[0.0002825967,0.0001109844,0.0002297534,0.002100784,0.00002948973,0.00001133808,6.529116e-7,0.9714593,0.0002664088,0.02159288,0.003178942,0.0007368746],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002736497,0.0001736474,0.9953573,0.0002443027,0.002531649,0.0003169948,0.00039729,0.0001262483,0.000578928],"genre_scores_gemma":[0.106473,0.00004105798,0.8901252,0.000763202,0.001485762,0.000007188166,0.0008458116,0.00005209784,0.000206711],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9909882,"threshold_uncertainty_score":0.9997569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1140113605752562,"score_gpt":0.2911063442832601,"score_spread":0.1770949837080039,"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."}}