{"id":"W3096792928","doi":"10.5267/j.msl.2020.10.013","title":"Enhancing business entrepreneurship through open government data","year":2020,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Organizational and Employee Performance","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Competitor analysis; Entrepreneurship; Government (linguistics); Business; Sample (material); Quality (philosophy); State (computer science); Marketing; Finance; Computer science","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":["scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0004314195,0.0001304807,0.0001077377,0.00002824506,0.0003558208,0.001078185,0.009758465,0.000009885493,0.00003299586],"category_scores_gemma":[0.00003862737,0.0001185147,0.00001117664,0.002197545,0.0001356128,0.005188088,0.01003848,0.00006395665,0.0002459686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007767322,"about_ca_system_score_gemma":0.00002347152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002049526,"about_ca_topic_score_gemma":0.000002070867,"domain_scores_codex":[0.9974236,0.00001814376,0.0001941504,0.0009597828,0.001026548,0.0003777443],"domain_scores_gemma":[0.9986412,0.00001603411,0.0000810456,0.001135374,0.00002049689,0.000105828],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007578907,0.0006023866,0.1027978,0.0008109079,0.0002016684,0.0005951087,0.01176352,0.01763565,0.1970253,0.292244,0.2487884,0.1274596],"study_design_scores_gemma":[0.001954837,0.0001334315,0.2449047,0.0002261093,0.00006825643,0.000022592,0.0005138445,0.09689113,0.08663297,0.002057157,0.5644147,0.002180304],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01729787,0.00001109806,0.8005789,0.1733749,0.0005049336,0.0003818547,0.000005729368,0.0001600295,0.007684731],"genre_scores_gemma":[0.8141591,0.00004230757,0.1017512,0.08364245,0.0001616174,0.00001346893,0.000009646013,0.00001205857,0.0002081467],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7968612,"threshold_uncertainty_score":0.9999588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05086153917807523,"score_gpt":0.2576313273962782,"score_spread":0.206769788218203,"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."}}