{"id":"W2800955910","doi":"10.1136/bmj.k2133","title":"Trump promises to reduce drug prices but drops campaign promises","year":2018,"lang":"en","type":"article","venue":"BMJ","topic":"Pharmaceutical Economics and Policy","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Data science; Computer science; Drug; Drug prices; World Wide Web; Medicine; Pharmacology; Economics; Public economics","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":[0.01049163,0.001027816,0.0009253739,0.001458808,0.003512493,0.01051457,0.001283475,0.01168878,0.05785779],"category_scores_gemma":[0.07829451,0.0005103416,0.0008757359,0.001137313,0.004509578,0.009763496,0.003985365,0.0196367,0.01407772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005598727,"about_ca_system_score_gemma":0.006849108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009325423,"about_ca_topic_score_gemma":0.009507098,"domain_scores_codex":[0.9820946,0.004475505,0.0004684028,0.00111592,0.009994813,0.001850794],"domain_scores_gemma":[0.9733526,0.01232425,0.00187433,0.001597291,0.005548484,0.005303049],"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":[0.00009945433,0.00006905115,0.0004381064,0.00007043951,0.0000236195,0.00005463855,0.0001354282,0.0000730927,0.0001486871,0.06367223,0.9069526,0.02826254],"study_design_scores_gemma":[0.00008706851,0.0001331893,0.001371605,0.0002323734,0.00001775512,0.00006701097,0.0001824388,0.0003772813,0.000322557,0.0303122,0.9668595,0.00003711534],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001539427,0.004182902,0.0009189623,0.9228438,0.01407905,0.00002834958,0.0002086582,0.0001444277,0.05605434],"genre_scores_gemma":[0.07520279,0.005957839,0.003000308,0.7708525,0.03869469,0.0001669098,0.0004281507,0.0004928515,0.105204],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.05785779,"threshold_uncertainty_score":0.1935536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07459406788040011,"score_gpt":0.3305366650573484,"score_spread":0.2559425971769483,"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."}}