{"id":"W45620804","doi":"10.1533/9781908818089.17","title":"Background: drug approval, drug patenting, pharmaceutical linkage, and public health policy * *This chapter is based upon material in: M. Sawicka and R.A. Bouchard, ‘Empirical Analysis of Canadian Drug Approval Data 2001–2008: Are Canadian Pharmaceutical Players “Doing More With Less?”’ McGill Journal of Law & Health 3: 87–151 (2009); R.A. Bouchard, J. Sawani, C. McLelland, M. Sawicka, and R. Hawkins, ‘The Pas de Deux of Pharmaceutical Regulation and Innovation: Who’s Leading Whom?’ Berkeley Technology Law Journal 24(3): 1461–522 (2009); R.A. Bouchard, R.W. Hawkins, R. Clark, R. Hagtvedt, and J. Sawani, ‘Empirical Analysis of Drug Approval-Patenting Linkage for High Value Pharmaceuticals,’ Northwestern Journal of Technology & Intellectual Property 8(2): 1–86 (2010).","year":2012,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Pharmaceutical Economics and Policy","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Linkage (software); Record linkage; Public health; Drug; Political science; Public economics; Medicine; Economics; Pharmacology; Environmental health; Chemistry; Population","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000678776,0.0009160012,0.0006303083,0.002205675,0.002097602,0.004242391,0.001001511,0.003595387,0.05395174],"category_scores_gemma":[0.001381286,0.0004012224,0.0002815454,0.007083528,0.002931708,0.004025651,0.001139785,0.004038383,0.01268805],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004012031,"about_ca_system_score_gemma":0.004523617,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02565957,"about_ca_topic_score_gemma":0.02976968,"domain_scores_codex":[0.9994689,0.0001271626,0.00002016807,0.0001157539,0.0002028102,0.00006531495],"domain_scores_gemma":[0.9988874,0.0007476462,0.00005954216,0.00002993243,0.0001825305,0.0000929564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0000128952,0.00004360164,0.0002158288,0.0006997184,0.000004570818,0.00005799998,0.0003837989,0.0003756215,0.00006605266,0.3222681,0.5837923,0.09207946],"study_design_scores_gemma":[0.000003042047,0.000009732729,0.0007320922,0.001000509,0.000002671482,0.00007814366,0.000178348,0.0001398279,0.00003938118,0.05760418,0.9402027,0.000009370744],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.0009289014,0.5014861,0.002869398,0.09840409,0.004983484,0.00004764539,0.002018786,0.0001126385,0.3891489],"genre_scores_gemma":[0.02833048,0.5508377,0.004808764,0.04655009,0.02173907,0.0002142923,0.002496205,0.0001228611,0.3449005],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.995988,"threshold_uncertainty_score":0.1804866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1538024731212655,"score_gpt":0.3356335759039986,"score_spread":0.181831102782733,"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."}}