{"id":"W2912161163","doi":"10.1002/9781119214656.ch11","title":"Description of Datasets","year":2018,"lang":"en","type":"other","venue":"Wiley series in probability and statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Statistics Canada","funders":"","keywords":"Outlier; Multivariate statistics; Computer science; Data mining; Range (aeronautics); Anomaly detection; Artificial intelligence; Machine learning; Engineering","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":[0.000443884,0.0002273855,0.0005519524,0.00008091379,0.00002714517,0.00001348417,0.0001211408,0.0002194187,0.0006862965],"category_scores_gemma":[0.002437963,0.0002089368,0.00001928291,0.00008272455,0.0007340738,0.00006473831,0.0001069104,0.0001486756,0.000004249271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000295212,"about_ca_system_score_gemma":0.00004456665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000719152,"about_ca_topic_score_gemma":0.001221776,"domain_scores_codex":[0.9986037,0.0001784541,0.0004812934,0.0003584802,0.0001750996,0.0002029603],"domain_scores_gemma":[0.9986656,0.0005098285,0.0002551026,0.0004485259,0.00005547961,0.00006549463],"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":[0.00006261926,0.000117872,0.0001230058,0.00216865,0.00002133024,0.000006792621,0.0001383977,4.570225e-7,0.000006080482,0.7584944,0.2256289,0.0132315],"study_design_scores_gemma":[0.0001801734,0.0001534512,0.00003465269,0.0005353647,0.00003898182,0.000003944482,0.00002693739,0.0001577786,0.000009486182,0.9178413,0.08082758,0.0001903482],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00002817434,0.0002386234,0.9583568,0.00001182412,0.0002107788,0.0005135887,0.01382816,0.0000462903,0.02676578],"genre_scores_gemma":[0.00003242022,0.00062565,0.9685051,0.00001078005,0.00005278182,0.00002740517,0.0003045204,0.0001130996,0.0303282],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1593469,"threshold_uncertainty_score":0.8520195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1009599913770908,"score_gpt":0.3780561449761514,"score_spread":0.2770961535990606,"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."}}