{"id":"W2996627361","doi":"10.3390/jrfm12040188","title":"Influence of Venture Capital and Knowledge Transfer on Innovation Performance in the Big Data Environment","year":2019,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Private Equity and Venture Capital","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Venture capital; Prospectus; Business; Portfolio; Knowledge transfer; Social venture capital; Industrial organization; Profit (economics); Entrepreneurship; Investment (military); Marketing; Finance; Economics; Microeconomics; Management","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":[0.0007996013,0.00009751256,0.0001554951,0.0002661129,0.0000524161,0.00004369311,0.0002912896,0.00003949341,0.000004797192],"category_scores_gemma":[0.00002903585,0.0000672134,0.00002075855,0.000257261,0.00004231458,0.0005556103,0.0001769605,0.0002055628,0.000008972047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001173019,"about_ca_system_score_gemma":0.000008468045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001087189,"about_ca_topic_score_gemma":0.000009254396,"domain_scores_codex":[0.9992364,0.00001259681,0.0003157618,0.0001282314,0.0001983322,0.0001086753],"domain_scores_gemma":[0.9995742,0.00002352981,0.0001756485,0.000189376,0.00003217583,0.000005058444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000706233,0.0007742558,0.2998812,0.001289489,0.00005241939,0.00004404952,0.00278023,0.001774227,0.0002665692,0.1189964,0.0006417312,0.5727931],"study_design_scores_gemma":[0.0009820826,0.0001102527,0.9182913,0.0001709999,0.00005304498,0.000002960516,0.0003232278,0.0001383384,0.00001468009,0.001421174,0.0783947,0.00009723585],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983136,0.0004438387,0.0002279039,0.0001239677,0.0001915907,0.0001818486,0.000004649922,0.000001855981,0.0005107376],"genre_scores_gemma":[0.997822,0.001619023,0.00001887009,0.0002209415,0.0002955465,0.000001517859,0.000005896992,0.000004673232,0.00001154168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6184101,"threshold_uncertainty_score":0.2740883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01554947611666976,"score_gpt":0.2013734093663285,"score_spread":0.1858239332496587,"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."}}