{"id":"W4388247556","doi":"10.1002/for.2868","title":"Issue Information","year":2023,"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":"McGill University; University of Waterloo","funders":"","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":[0.001408037,0.001150185,0.001472542,0.003307908,0.001416884,0.005375163,0.001906301,0.002309257,0.9490265],"category_scores_gemma":[0.01169276,0.0005260658,0.0007988224,0.003230601,0.0003740034,0.003181372,0.00186539,0.001812765,0.8946078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001229825,"about_ca_system_score_gemma":0.002134219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001971229,"about_ca_topic_score_gemma":0.003812083,"domain_scores_codex":[0.9987489,0.0001443078,0.0001075744,0.000180616,0.0006449157,0.0001736043],"domain_scores_gemma":[0.9933322,0.001052619,0.0002517019,0.0007805401,0.003184332,0.001398566],"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":[0.00002964231,0.00001804295,0.00004211531,0.0001161712,0.00000142522,0.00001326321,0.000007462619,0.00002053891,0.00005960256,0.0007662044,0.9792087,0.0197167],"study_design_scores_gemma":[0.00001623632,0.00001683546,0.0002009118,0.000104152,0.000001825195,0.00002165701,0.00001907721,0.00004935403,0.00007974948,0.0005980111,0.9988882,0.000004154153],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003784656,0.000704913,0.0009413597,0.005600915,0.01874973,0.0005803834,0.06097629,0.002468135,0.9095997],"genre_scores_gemma":[0.001272334,0.0004596866,0.0003494172,0.001322365,0.001620694,0.0001536203,0.01597975,0.0006199165,0.9782223],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05097353,"threshold_uncertainty_score":0.07270747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0849245082485779,"score_gpt":0.2355550869269293,"score_spread":0.1506305786783514,"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."}}