{"id":"W7096731832","doi":"","title":"1 Prescription Drug Importation, Investment and Employment in Michigan","year":2004,"lang":"en","type":"article","venue":"","topic":"Pharmaceutical Economics and Policy","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medical prescription; Prescription drug; Authorization; Investment (military); Drug prices; Profit (economics); Developed country; Legislation","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":[0.0003189289,0.0001298385,0.0001142709,0.0007206234,0.003227985,0.001958671,0.0004665909,0.0012529,0.01999035],"category_scores_gemma":[0.001263697,0.0001455551,0.0001473956,0.001423021,0.0005034959,0.001000263,0.001109127,0.001321461,0.0008817679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004388458,"about_ca_system_score_gemma":0.002974598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1021172,"about_ca_topic_score_gemma":0.317885,"domain_scores_codex":[0.9997047,0.00005790709,0.00000913373,0.00002561725,0.00008255175,0.0001199922],"domain_scores_gemma":[0.9990637,0.0003072104,0.0001714854,0.00001486954,0.00009292051,0.0003498119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001889258,0.0006746521,0.4444413,0.0001225395,0.00006134142,0.002867487,0.002758702,0.001232479,0.0005576868,0.1753867,0.3068705,0.06483769],"study_design_scores_gemma":[0.00004405319,0.0001749606,0.6097364,0.0002424403,0.00003941727,0.0007596003,0.005556533,0.004077243,0.0006672948,0.01928783,0.3593608,0.00005345286],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5338947,0.005776081,0.0003008361,0.09532571,0.0002381574,0.00008597483,0.004710776,0.00004879828,0.359619],"genre_scores_gemma":[0.8164539,0.006958383,0.0003684595,0.006582456,0.0004568986,0.0001595732,0.001524257,0.00001742747,0.1674787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1021172,"threshold_uncertainty_score":0.2030456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04145971896364928,"score_gpt":0.2684537624425883,"score_spread":0.226994043478939,"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."}}