{"id":"W4390923943","doi":"10.15804/ksm20230403","title":"Using Artificial Intelligence in Public Management: Aspects of Integration","year":2023,"lang":"en","type":"article","venue":"Krakowskie Studia Małopolskie","topic":"Economic Issues in Ukraine","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Public service; Knowledge management; Adaptability; Flexibility (engineering); Business; Engineering; Public relations; Political science; Computer science; Economics; Management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001078426,0.0002117743,0.0005223677,0.001098767,0.00008412429,0.00006375094,0.0004142674,0.0001068513,0.0003754051],"category_scores_gemma":[0.0002357262,0.0002700819,0.0001140862,0.001558834,0.0001468079,0.0003381669,0.0002609236,0.0001875323,0.001045046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00026974,"about_ca_system_score_gemma":0.00003032431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001829218,"about_ca_topic_score_gemma":0.0002811334,"domain_scores_codex":[0.9977406,0.00002801925,0.00112837,0.0005409668,0.0000634051,0.0004986677],"domain_scores_gemma":[0.9989257,0.00009362629,0.0003999595,0.0004789314,0.00003749111,0.0000642755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000007703652,0.00009648022,0.0001039301,0.00004225237,0.0000574748,0.00002060599,0.0007962966,0.0004933615,0.00002813632,0.9941001,0.00007772825,0.004175928],"study_design_scores_gemma":[0.0001623177,0.00003880947,0.001515831,0.00004190267,0.000006406796,0.000001837633,0.000804878,0.009485465,0.0004003346,0.9844011,0.002880636,0.000260466],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.002903332,0.0004343301,0.003767896,0.0005659886,0.0008559148,0.0004067841,0.00005546595,0.00009052548,0.9909198],"genre_scores_gemma":[0.9966244,0.0003223204,0.002488243,0.00005149098,0.0001373538,0.00004213408,0.00002720353,0.00003977573,0.0002670858],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9937211,"threshold_uncertainty_score":0.9999751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.164225385117679,"score_gpt":0.3111023704558793,"score_spread":0.1468769853382003,"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."}}