{"id":"W4247732613","doi":"10.1111/ciso.12090","title":"Issue Information ‐ TOC","year":2017,"lang":"en","type":"paratext","venue":"City & Society","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University; University of Toronto","funders":"","keywords":"Citation; Information retrieval; Computer 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000520293,0.0002524799,0.0006539489,0.00006320094,0.0005928251,0.0005259071,0.0006034214,0.0003743455,0.07351816],"category_scores_gemma":[0.00006440675,0.0003034975,0.0005309493,0.00006013404,0.0002272463,0.0008266898,0.0003071416,0.0002993595,0.5900015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002541635,"about_ca_system_score_gemma":0.00004762175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003732775,"about_ca_topic_score_gemma":0.000005251404,"domain_scores_codex":[0.9985842,0.000003871809,0.0005880247,0.0004242641,0.00004028624,0.000359397],"domain_scores_gemma":[0.9982105,0.00001993237,0.0009414358,0.0006931916,0.0000540931,0.00008085248],"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":[0.000001719872,0.00001242954,0.0001075955,0.00007034399,0.0001455735,8.74722e-8,0.002217387,0.00001363619,5.929629e-8,0.001217767,0.9957655,0.0004479224],"study_design_scores_gemma":[0.0002730851,0.000009107641,0.0002619311,0.00002198127,0.000009508502,3.502083e-7,0.0005909876,0.0001670272,0.000003231916,0.0004087145,0.9979139,0.000340151],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001805332,0.002561399,0.0004014231,0.0003658928,0.02222914,0.000230232,0.003948239,0.00002839104,0.9700547],"genre_scores_gemma":[0.001143379,0.004078499,0.000241368,0.0008511343,0.0007805662,0.00003103353,0.0004065846,0.00001566834,0.9924518],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5164834,"threshold_uncertainty_score":0.9999417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04903645408444375,"score_gpt":0.2374976581888026,"score_spread":0.1884612041043588,"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."}}