{"id":"W2206422764","doi":"","title":"Big data Analysis: The n ext f rontier","year":2013,"lang":"en","type":"article","venue":"Bank of Canada review","topic":"Big Data Technologies and Applications","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Exploit; Big data; Complement (music); Inflation (cosmology); Set (abstract data type); Data science; Economics; Computer science; Data mining; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001258448,0.00007238768,0.0003325488,0.00004844118,0.00009078255,0.00005469438,0.003805012,0.00002357429,0.001185851],"category_scores_gemma":[0.001467788,0.00003512067,0.00006579326,0.001934218,0.00007915649,0.0001286514,0.0005549847,0.0000726953,0.0000563272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001443043,"about_ca_system_score_gemma":0.0003211817,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1914941,"about_ca_topic_score_gemma":0.4925815,"domain_scores_codex":[0.9981862,0.00006033008,0.0005258228,0.0003060409,0.0007792006,0.0001423859],"domain_scores_gemma":[0.9950203,0.0002674632,0.000274576,0.004201445,0.0001895795,0.00004661814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[4.707001e-8,0.000002339831,0.00008703877,0.00000991129,0.00002626122,1.111713e-7,4.70019e-7,6.492829e-7,0.000001406575,0.0007331911,0.6210644,0.3780741],"study_design_scores_gemma":[0.00001367514,0.000001982344,0.00591808,0.00004599835,0.0001650294,7.503371e-7,0.00005113221,0.0002162123,0.000006575397,0.001511583,0.9920208,0.00004818982],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.0009483947,0.7013714,0.01272002,0.265867,0.0004151028,0.001686131,0.001167333,0.00005185668,0.01577277],"genre_scores_gemma":[0.7540415,0.2009665,0.005961624,0.02504527,0.000239557,0.0005146944,0.0004298351,0.00002951212,0.01277152],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.7530931,"threshold_uncertainty_score":0.9997272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3562913429076259,"score_gpt":0.3743734165200423,"score_spread":0.01808207361241637,"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."}}