{"id":"W3122232577","doi":"10.1111/jems.12048","title":"Behind the Scenes: Sources of Complementarity in R&D","year":2014,"lang":"en","type":"article","venue":"Journal of Economics & Management Strategy","topic":"Innovation Policy and R&D","field":"Economics, Econometrics and Finance","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"","keywords":"Complementarity (molecular biology); Economies of scope; Absorptive capacity; Panel data; Industrial organization; Business; Scope (computer science); Microeconomics; Economics; Monetary economics; Econometrics; Computer science; Economies of scale","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":[0.004105088,0.0003522215,0.001251517,0.003498127,0.001876778,0.005504678,0.001014344,0.001239064,0.01795654],"category_scores_gemma":[0.02258235,0.0006336892,0.001037404,0.005269333,0.002484224,0.003501114,0.003857872,0.00217607,0.00106037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003272115,"about_ca_system_score_gemma":0.003039694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01712179,"about_ca_topic_score_gemma":0.01936317,"domain_scores_codex":[0.9945372,0.00144015,0.0002356204,0.001080864,0.001723473,0.0009827099],"domain_scores_gemma":[0.9623738,0.0244588,0.007020359,0.002328551,0.002607946,0.001210545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007131153,0.0004279017,0.5962989,0.0007497095,0.0008225291,0.001791721,0.004238641,0.01424453,0.003255546,0.2333353,0.0105604,0.1335617],"study_design_scores_gemma":[0.0001565779,0.0002077239,0.6036596,0.0004719541,0.0006392335,0.0009609709,0.007897132,0.027329,0.004131581,0.3172326,0.03708645,0.0002271722],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9005778,0.003567393,0.01994108,0.009523006,0.00006396749,0.0001277394,0.001683156,0.0002146071,0.06430119],"genre_scores_gemma":[0.9962093,0.0003064983,0.0009409969,0.0003036915,0.00003851199,0.00001594762,0.0002722807,0.0000229381,0.001889936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01795654,"threshold_uncertainty_score":0.06007057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07821299470206565,"score_gpt":0.2635051436610801,"score_spread":0.1852921489590144,"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."}}