{"id":"W2609180639","doi":"10.3386/w25928","title":"Scientific Education and Innovation: From Technical Diplomas to University STEM Degrees","year":2019,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Economics; Mathematics education; Engineering management; Engineering; Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001098586,0.0001612794,0.0003166684,0.00105633,0.0006157415,0.001951334,0.0003889645,0.0007050329,0.01253766],"category_scores_gemma":[0.007157894,0.00008664726,0.0005194571,0.002128832,0.00067871,0.0008731197,0.00138028,0.0008837176,0.000790419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001729328,"about_ca_system_score_gemma":0.003202145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01919847,"about_ca_topic_score_gemma":0.01921539,"domain_scores_codex":[0.9990403,0.000261881,0.00003392521,0.0001287082,0.0002008838,0.0003341978],"domain_scores_gemma":[0.9914514,0.004811008,0.002030598,0.000146553,0.0004404118,0.001120055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002654401,0.004404286,0.6500379,0.001042745,0.0002791532,0.001379887,0.002668628,0.008090017,0.001938441,0.06291196,0.02179241,0.2428001],"study_design_scores_gemma":[0.0002626494,0.0007998472,0.9526741,0.0001928264,0.0002287439,0.0001590701,0.00261123,0.001491042,0.001692612,0.0149878,0.02487733,0.00002272619],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9303288,0.003451247,0.0003426676,0.007119764,0.0001065913,0.00003233401,0.0008407612,0.00001729141,0.05776057],"genre_scores_gemma":[0.9921784,0.001483262,0.0001244869,0.0005011214,0.0001463441,0.00002122198,0.000400382,0.0000053587,0.00513939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01919847,"threshold_uncertainty_score":0.04194266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4391429701143855,"score_gpt":0.4617514671142401,"score_spread":0.02260849699985468,"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."}}