{"id":"W2598117174","doi":"","title":"Public Innovation Policy and Other Determinants of Innovativeness in Poland","year":2016,"lang":"en","type":"article","venue":"˜The œinnovation journal","topic":"Regional Development and Policy","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economics; Romer; Total factor productivity; Human capital; Innovation economics; Technological change; Revenue; Productivity; Per capita; Technical progress; Per capita income; Endogenous growth theory; Technical change; Value (mathematics); Growth accounting; Macroeconomics; Economic growth; Population","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009853584,0.0001392253,0.0003779302,0.001522878,0.0004755888,0.00236641,0.0002722748,0.0004986737,0.006733604],"category_scores_gemma":[0.005153449,0.0001284747,0.0005170975,0.001751244,0.0005874918,0.001068023,0.00138621,0.0008191348,0.0004678984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001629066,"about_ca_system_score_gemma":0.002156915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007893321,"about_ca_topic_score_gemma":0.006002133,"domain_scores_codex":[0.9995046,0.00006420505,0.00004580911,0.00006897451,0.0001119238,0.0002046546],"domain_scores_gemma":[0.9957182,0.0009471019,0.002213337,0.0001819677,0.0003497713,0.0005895134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002263392,0.0005028005,0.9544922,0.0002018337,0.0002068192,0.0004672235,0.001299741,0.001804973,0.0005241317,0.008423295,0.001434185,0.03041655],"study_design_scores_gemma":[0.00002688036,0.00008106442,0.99033,0.0001078984,0.00007163496,0.00009627189,0.001811418,0.00102642,0.0001634191,0.00252492,0.003750523,0.000009412444],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925709,0.0005507423,0.0001319186,0.0008797947,0.000006705378,0.00002187679,0.0001920341,0.000006826072,0.005639107],"genre_scores_gemma":[0.9982885,0.000353446,0.000038791,0.0000367448,0.000008281275,0.000009998999,0.00008746099,0.000001753617,0.001174926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007893321,"threshold_uncertainty_score":0.02252614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1037943940361998,"score_gpt":0.3662814872411551,"score_spread":0.2624870932049553,"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."}}