{"id":"W2051037209","doi":"10.2307/2667019","title":"Making the Next Move: How Experiential and Vicarious Learning Shape the Locations of Chains' Acquisitions","year":2000,"lang":"en","type":"article","venue":"Administrative Science Quarterly","topic":"Outsourcing and Supply Chain Management","field":"Business, Management and Accounting","cited_by":759,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; University of Toronto","funders":"","keywords":"Experiential learning; Perspective (graphical); Observational learning; Knowledge management; Organizational learning; Business; Psychology; Computer science; Artificial intelligence; Mathematics education","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009075989,0.0001329844,0.0001542848,0.0009963324,0.001754703,0.002973315,0.0007873189,0.0005880713,0.004655684],"category_scores_gemma":[0.007100317,0.0001565468,0.0001858813,0.00106442,0.004355288,0.003909203,0.00242869,0.0005974547,0.0003119593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004305698,"about_ca_system_score_gemma":0.002654835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05610183,"about_ca_topic_score_gemma":0.1203347,"domain_scores_codex":[0.9994196,0.0001941903,0.00001823595,0.0001035549,0.0001023811,0.0001621441],"domain_scores_gemma":[0.9960902,0.001443959,0.001070029,0.0003957856,0.0003955899,0.0006044343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004066994,0.0003287217,0.6915279,0.0001074539,0.00005970098,0.001354152,0.07916007,0.01228699,0.005258243,0.07625679,0.0008961713,0.1323571],"study_design_scores_gemma":[0.00004492404,0.0002753318,0.7800472,0.0001749691,0.00005334618,0.0004538635,0.09872123,0.01847712,0.002832223,0.07880052,0.02001185,0.0001074504],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981371,0.00009352801,0.003553649,0.0004155053,0.000002390814,0.00001035304,0.00003459976,0.00001179807,0.01450728],"genre_scores_gemma":[0.9987783,0.00003017621,0.0005013367,0.000009683125,8.758287e-7,0.000003344886,0.00001483227,0.000002770962,0.0006587474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05610183,"threshold_uncertainty_score":0.1115506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03623705596399512,"score_gpt":0.2849482451570221,"score_spread":0.248711189193027,"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."}}