{"id":"W4244236454","doi":"10.1002/sam.11386","title":"Issue Information","year":2019,"lang":"en","type":"paratext","venue":"Statistical Analysis and Data Mining The ASA Data Science Journal","topic":"Transportation Systems and Logistics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; Université de Montréal","funders":"","keywords":"Computer science; Information retrieval; Citation; Data science; World Wide Web; Library science","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":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002762828,0.0002172758,0.0004685319,0.0004236654,0.0004450563,0.001564224,0.003378693,0.00009011688,0.001485418],"category_scores_gemma":[0.0003619498,0.000136451,0.00003111105,0.001117657,0.0004104448,0.002660539,0.0005372377,0.0005142207,0.001185022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003145794,"about_ca_system_score_gemma":0.0002357862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001285389,"about_ca_topic_score_gemma":0.00007463417,"domain_scores_codex":[0.9976445,0.00004136755,0.0007516591,0.0003841106,0.0008286202,0.0003496908],"domain_scores_gemma":[0.9970503,0.0002888144,0.0002609981,0.002044495,0.0001537838,0.0002016012],"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":[0.000005483467,0.000006620901,0.0003411956,0.0001005828,0.0005355849,0.000004876382,0.0003478975,0.006673734,0.00000539641,0.0003442851,0.9620035,0.02963085],"study_design_scores_gemma":[0.00009982035,0.00001639193,0.004506537,0.00004697273,0.0008820985,0.00002655064,0.0007425482,0.3660646,6.984091e-7,0.00001638408,0.6273673,0.0002300797],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001939625,0.0006601235,0.9379987,0.0001377278,0.002784402,0.0001020052,0.05309363,0.00001918584,0.005010272],"genre_scores_gemma":[0.3835256,0.01818909,0.266245,0.001080714,0.004788039,0.00001300783,0.315743,0.0001360515,0.01027947],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6717536,"threshold_uncertainty_score":0.9995927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04854510382062079,"score_gpt":0.3262234257958047,"score_spread":0.2776783219751839,"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."}}