{"id":"W187770969","doi":"","title":"ВЕНЧУРНЫЕ ФОНДЫ В ЭКОНОМИКЕ ВЫСОКИХ ТЕХНОЛОГИЙ (ПРИМЕР КАНАДЫ)","year":2001,"lang":"ru","type":"article","venue":"id = 542, shortTitle = MEO, editionType = 2, dateBegin = 1957-08-01 00:00:00.0, officeEncoding = Cp1251, officeStatus = 1, loadType = 1, langId = Russian","topic":"Economic Systems and Logistics Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Venture capital; Capital (architecture); Business; Management; Finance; Economics; Political science; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.004622297,0.00324593,0.004367073,0.002758574,0.002048543,0.002358848,0.003682741,0.002225241,0.03568924],"category_scores_gemma":[0.000876072,0.00380186,0.001600709,0.00266586,0.001115796,0.002449816,0.001223232,0.002823748,0.0496671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002296708,"about_ca_system_score_gemma":0.0009703147,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007563686,"about_ca_topic_score_gemma":0.004206797,"domain_scores_codex":[0.9820067,0.0005559932,0.005950467,0.005270542,0.001212704,0.005003589],"domain_scores_gemma":[0.9871596,0.001011015,0.00447482,0.004799046,0.0005169377,0.002038581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0010758,0.003363789,0.02275658,0.002117211,0.003078169,0.001642915,0.002501547,0.003190116,0.0001819736,0.1837844,0.7700549,0.00625263],"study_design_scores_gemma":[0.004385531,0.0008692228,0.02090323,0.001259088,0.0005818906,0.000234047,0.002491517,0.00715129,0.0000957116,0.00358003,0.9534494,0.00499903],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02943956,0.02954289,0.00569509,0.005372358,0.0412852,0.004880796,0.01288504,0.001711644,0.8691874],"genre_scores_gemma":[0.8978412,0.01652453,0.002192908,0.001872631,0.01294136,0.0004549772,0.007946418,0.001041501,0.05918446],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8684016,"threshold_uncertainty_score":0.9994768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03887030804029842,"score_gpt":0.2450293022766279,"score_spread":0.2061589942363294,"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."}}