{"id":"W3124472169","doi":"10.24149/gwp268","title":"Big Data Analytics: A New Perspective","year":2016,"lang":"en","type":"article","venue":"Federal Reserve Bank of Dallas, Globalization and Monetary Policy Institute Working Papers","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity College","funders":"","keywords":"Covariate; Computer science; Statistical inference; Context (archaeology); Inference; Econometrics; Statistical hypothesis testing; Model selection; Data mining; Toolbox; Set (abstract data type); Machine learning; Artificial intelligence; Statistics; 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":[0.00033229,0.0002536702,0.000406698,0.00016178,0.0001733093,0.00008307014,0.0004968977,0.0001260923,0.00007617899],"category_scores_gemma":[0.005647162,0.0001835972,0.00006528683,0.0004438926,0.0002864761,0.0001806304,0.0003442245,0.0000929892,0.000005091259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001361665,"about_ca_system_score_gemma":0.0003448847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004393427,"about_ca_topic_score_gemma":0.002393914,"domain_scores_codex":[0.9981017,0.0001347763,0.000496172,0.0005164326,0.0003877445,0.000363139],"domain_scores_gemma":[0.998265,0.0003975051,0.0002386645,0.0007135613,0.0001192733,0.0002659627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001113333,0.00005402241,0.005213384,0.00005721821,0.0001643794,0.000008409773,0.000221831,0.00002913717,0.0004399353,0.8907781,0.005509923,0.09741236],"study_design_scores_gemma":[0.003955812,0.0003864717,0.02129541,0.001610565,0.0002738767,0.00004009157,0.0004728154,0.003259412,0.0002981706,0.7442104,0.2230884,0.001108587],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04266466,0.002467597,0.5556175,0.03159268,0.002115213,0.001665226,0.001206556,0.0005011323,0.3621694],"genre_scores_gemma":[0.9205545,0.001314601,0.0743512,0.0007793172,0.0008272171,0.000004683213,0.00006843648,0.00003403517,0.002065983],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8778899,"threshold_uncertainty_score":0.7486878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2037723058995163,"score_gpt":0.3833688596067316,"score_spread":0.1795965537072153,"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."}}