{"id":"W4328025185","doi":"10.5267/j.uscm.2023.1.015","title":"The effect of strategic intelligence, effective decision-making and strategic flexibility on logistics performance","year":2023,"lang":"en","type":"article","venue":"Uncertain Supply Chain Management","topic":"Organizational and Employee Performance","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Flexibility (engineering); Business; Futures studies; Strategic planning; Process management; General partnership; Affect (linguistics); Strategic thinking; Strategic sourcing; Knowledge management; Strategic financial management; Marketing; Computer science; Management; Economics; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001485661,0.0002232127,0.0002059397,0.0001843138,0.0004006565,0.0001576076,0.0007835766,0.00004762508,0.000008567687],"category_scores_gemma":[0.00005376522,0.000143188,0.00004707467,0.001221665,0.0001761424,0.0001356867,0.0004448945,0.0001489477,0.00007301277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007870121,"about_ca_system_score_gemma":0.00002374597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008618453,"about_ca_topic_score_gemma":0.000006623283,"domain_scores_codex":[0.9982095,0.0001385916,0.0003261022,0.0004695377,0.000483325,0.0003729562],"domain_scores_gemma":[0.9975842,0.001603921,0.0001114254,0.0005762643,0.00006879225,0.00005542284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002684991,0.00006170314,0.01763603,0.0006211362,0.0001357958,0.00004565627,0.00043714,0.2075061,0.00001875782,0.4491788,0.0002491602,0.3238412],"study_design_scores_gemma":[0.0003661322,0.001624279,0.02809339,0.0003254705,0.00002700736,0.000004632927,0.000324064,0.82251,0.0008547737,0.1453588,0.0001838203,0.0003275703],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9438332,0.0001294915,0.04757838,0.0003876215,0.0005486481,0.001235086,0.000008026834,0.0002378501,0.006041719],"genre_scores_gemma":[0.9980568,0.0003666023,0.001218353,0.00005685212,0.00004033962,0.0000702448,0.000005540288,0.00001153675,0.000173714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6150039,"threshold_uncertainty_score":0.5839036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02734771899557824,"score_gpt":0.2850165199977148,"score_spread":0.2576688010021366,"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."}}