{"id":"W3125844636","doi":"","title":"Does Intellectual Property Lead to Economic Growth? Insights from an Improved IP Dataset","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; McGill University","funders":"","keywords":"Intellectual property; Context (archaeology); Incentive; Order (exchange); Index (typography); Empirical evidence; Causality (physics); Economics; Value (mathematics); Developing country; Lead (geology); Business; International trade; Law and economics; Industrial organization; Microeconomics; Political science; Computer science; Economic growth; Law","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006626862,0.0003340113,0.0003182344,0.0002258258,0.00151101,0.001678525,0.001625879,0.0001239225,0.0005951749],"category_scores_gemma":[0.0005344861,0.0001690746,0.000105209,0.00006771596,0.000094093,0.003281484,0.0004127347,0.001328123,0.00296626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003896379,"about_ca_system_score_gemma":0.0004929205,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01197602,"about_ca_topic_score_gemma":0.02570982,"domain_scores_codex":[0.9971698,0.00003660479,0.0004095866,0.0005112521,0.0001987493,0.001674036],"domain_scores_gemma":[0.9987708,0.00004043983,0.0003307793,0.0006569481,0.0001438066,0.00005718358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01392681,0.002492584,0.0158767,0.000300873,0.004292657,0.0001971074,0.006546681,0.0002269275,0.04099748,0.09385145,0.2285341,0.5927566],"study_design_scores_gemma":[0.004742392,0.001213463,0.002344244,0.0002345775,0.000422208,0.00009939243,0.004256539,0.03076143,0.00467803,0.3360218,0.6123709,0.002855006],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838503,0.0002147583,0.001901211,0.004714272,0.002770718,0.0006177098,0.0001037778,0.0001157332,0.005711539],"genre_scores_gemma":[0.990748,0.0002358683,0.00003708912,0.002139415,0.004141167,0.00001239872,0.0003013388,0.00005756844,0.00232714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5899016,"threshold_uncertainty_score":0.9997889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04773247266003818,"score_gpt":0.2400176631350077,"score_spread":0.1922851904749696,"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."}}