{"id":"W4415270187","doi":"10.32614/cran.package.medxr","title":"MedxR: Access Drug Regulatory Data via FDA and Health Canada APIs","year":2025,"lang":"","type":"dataset","venue":"","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Drug; Product (mathematics); Regulatory science; Public health; Open data; Data sharing; Cover (algebra); Data collection; Regulatory authority","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":[0.002988055,0.001985735,0.001472559,0.006515884,0.001389878,0.004073957,0.004025087,0.001669107,0.09032279],"category_scores_gemma":[0.01709456,0.001297193,0.001483528,0.01343902,0.0006428231,0.002346485,0.003092863,0.002882172,0.1101174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01227326,"about_ca_system_score_gemma":0.0257668,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6060147,"about_ca_topic_score_gemma":0.6569288,"domain_scores_codex":[0.9960867,0.0003977694,0.0003333528,0.0006465046,0.001963181,0.0005724882],"domain_scores_gemma":[0.9874822,0.001610152,0.001021502,0.002622726,0.006003655,0.001259638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000048783,0.00001084736,0.0004908763,0.0001194805,0.0000136795,0.000007674091,0.0000088119,0.0001587502,0.00004037871,0.000616316,0.9961362,0.002348127],"study_design_scores_gemma":[0.0001763287,0.000008918853,0.003787837,0.0001404287,0.00001621397,0.00002315758,0.00003936444,0.0007455468,0.0004476605,0.001236054,0.99334,0.000038561],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008759055,0.00004643681,0.0001965371,0.0001474292,0.00001552571,0.00002404283,0.9956759,0.00137389,0.002432673],"genre_scores_gemma":[0.0005044351,0.00007623228,0.0007000503,0.000117529,0.000007273209,0.00006899095,0.9968267,0.0003086566,0.001390105],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6060147,"threshold_uncertainty_score":0.7926112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4625360265914967,"score_gpt":0.4884421027771524,"score_spread":0.02590607618565571,"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."}}