{"id":"W4252446806","doi":"10.1002/for.2493","title":"Issue Information","year":2018,"lang":"en","type":"paratext","venue":"Journal of Forecasting","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Waterloo","funders":"Russian Academy of Sciences","keywords":"Computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001576686,0.00111171,0.001503719,0.003305998,0.001459097,0.005540296,0.002002161,0.002249186,0.9554191],"category_scores_gemma":[0.01452274,0.0004860216,0.0008466415,0.003253765,0.0003716121,0.003502491,0.00206768,0.001816957,0.8918945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001191282,"about_ca_system_score_gemma":0.002149513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001609007,"about_ca_topic_score_gemma":0.003059717,"domain_scores_codex":[0.9986351,0.0001694654,0.000126253,0.000208892,0.000667397,0.0001928684],"domain_scores_gemma":[0.9923145,0.001281254,0.0003016278,0.0009595655,0.00354194,0.001601159],"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":[0.00003201415,0.00001916486,0.00004653232,0.0001299286,0.00000176629,0.00001336412,0.00000849718,0.00002105569,0.00005407618,0.0007488602,0.9783886,0.0205362],"study_design_scores_gemma":[0.00001643256,0.00001756632,0.0001914539,0.0001220005,0.000002096798,0.000023104,0.00002153917,0.00004850647,0.00007797391,0.0006818862,0.9987932,0.000004098677],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005216715,0.001053478,0.001198354,0.007517251,0.0243018,0.0006736493,0.08288269,0.003224477,0.8786266],"genre_scores_gemma":[0.001879369,0.0006834477,0.0004375772,0.001645669,0.002075223,0.0001983794,0.02281584,0.0008314532,0.9694332],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04458094,"threshold_uncertainty_score":0.06358922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06501866908122084,"score_gpt":0.2285276088226783,"score_spread":0.1635089397414575,"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."}}