{"id":"W4389037139","doi":"10.1016/j.techfore.2023.123036","title":"Developing foresight that impacts senior management decisions","year":2023,"lang":"en","type":"article","venue":"Technological Forecasting and Social Change","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; University of Ottawa","funders":"National Research University Higher School of Economics; United Nations Educational, Scientific and Cultural Organization","keywords":"Futures studies; Delphi method; Delphi; Senior management; Decision maker; Government (linguistics); Knowledge management; Business; Management; Marketing; Management science; Computer science; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002952308,0.0002249269,0.0004450757,0.0007550337,0.001157915,0.000395798,0.0006542237,0.0002615246,0.00006690716],"category_scores_gemma":[0.002038161,0.000146911,0.0001501633,0.002249747,0.0001969837,0.000193615,0.001183418,0.0002239024,0.0002448056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006164953,"about_ca_system_score_gemma":0.0000116624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000226132,"about_ca_topic_score_gemma":0.00005708751,"domain_scores_codex":[0.9968165,0.0001055583,0.0005663862,0.0006542123,0.001240539,0.0006168137],"domain_scores_gemma":[0.9974195,0.001807025,0.0002277697,0.0003273337,0.0001196689,0.00009872438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001870564,0.0000135669,0.004048618,0.00001207336,0.00001703838,0.0001857748,0.001700551,0.000001324644,0.00001968433,0.2152807,0.006046397,0.7726556],"study_design_scores_gemma":[0.0005973543,0.00008847182,0.1085229,0.0002087759,0.00001787564,0.00007244599,0.009561933,0.006027836,0.00004225026,0.7755558,0.09874023,0.0005641585],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9746994,0.0003960571,0.01555407,0.003528548,0.0003993094,0.000600297,0.00002225193,0.001242025,0.003557989],"genre_scores_gemma":[0.995257,0.00004214691,0.003366853,0.0002362139,0.0001727279,0.0000803524,0.000003429709,0.00001667157,0.0008246325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7720914,"threshold_uncertainty_score":0.8905865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6345302880532125,"score_gpt":0.4369865528064399,"score_spread":0.1975437352467727,"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."}}