{"id":"W3087920976","doi":"10.5539/ibr.v13n10p108","title":"The Success of Business Forecasting: Comparisons across Industries, Countries and Time","year":2020,"lang":"en","type":"article","venue":"International Business Research","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Harvard Business School","keywords":"Manufacturing; German; Relevance (law); Economics; Business; Marketing; Industrial organization; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008628435,0.0004038298,0.0006330361,0.006473348,0.000475325,0.003467087,0.0005557943,0.0007722548,0.001266905],"category_scores_gemma":[0.06411143,0.0002124534,0.0007335728,0.009139268,0.0007782488,0.005271406,0.001453374,0.001036524,0.0007397383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00061659,"about_ca_system_score_gemma":0.0004968544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005921636,"about_ca_topic_score_gemma":0.00461337,"domain_scores_codex":[0.9959121,0.001406559,0.0004179671,0.0006523444,0.001089792,0.0005212629],"domain_scores_gemma":[0.9099669,0.05648566,0.0188516,0.005212012,0.007934279,0.001549611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002057941,0.00003726369,0.9183437,0.00009233668,0.0003283791,0.0001405827,0.001076087,0.0170136,0.0001603282,0.001926478,0.001607032,0.05906843],"study_design_scores_gemma":[0.00001495285,0.0002175427,0.9603907,0.0001880292,0.0001453798,0.0002198551,0.003544426,0.02277131,0.0007547166,0.003452067,0.008224439,0.00007643025],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726107,0.004100246,0.004728163,0.001207753,0.0001152192,0.0000190686,0.001552828,0.0001033231,0.01556265],"genre_scores_gemma":[0.9967635,0.0008398737,0.0007232697,0.00002826099,0.00006860965,0.000004723197,0.001230318,0.00001749236,0.0003239878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008628435,"threshold_uncertainty_score":0.04563212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4049196909370765,"score_gpt":0.4887109331442283,"score_spread":0.08379124220715184,"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."}}