{"id":"W2061120801","doi":"10.1038/nbt1106-1324","title":"Democracy unleashed—unpacking the tooth fairy in drug industry R&D","year":2006,"lang":"en","type":"letter","venue":"Nature Biotechnology","topic":"Pharmaceutical Economics and Policy","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"National Institutes of Health","keywords":"Unpacking; Democracy; Drug; Drug industry; Political science; Biology; Biotechnology; Pharmacology; Philosophy; 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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0006063756,0.0005390676,0.0009565556,0.001119158,0.0001627006,0.0001229027,0.001554515,0.0133448,0.0004648464],"category_scores_gemma":[0.0002332298,0.0005136424,0.0002649034,0.0007353284,0.0003729845,0.0001219385,0.0003905361,0.023739,0.001122004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004611061,"about_ca_system_score_gemma":0.0000862843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00063144,"about_ca_topic_score_gemma":0.0004232143,"domain_scores_codex":[0.9967822,0.00004722156,0.001040408,0.001045684,0.00005841682,0.001026105],"domain_scores_gemma":[0.9978324,0.0002329658,0.0006638526,0.001193675,0.00002277331,0.00005437571],"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":[0.000003873822,0.00002822442,0.002043046,0.00004212325,0.00005341303,0.00005699691,0.00002310183,0.00001235787,0.000006216166,0.08118957,0.9156849,0.0008561963],"study_design_scores_gemma":[0.0003451277,0.000009174583,0.0007682046,0.00002899687,0.00001010085,0.00002047787,0.000005829191,0.00007698061,0.00008373252,0.1204733,0.8776745,0.000503687],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01302906,0.007894253,0.00003677064,0.9498451,0.002256759,0.0004123486,0.0005246342,0.0001662493,0.0258348],"genre_scores_gemma":[0.1258925,0.0007299827,0.0002952887,0.8599289,0.00357419,0.00005699627,0.0003017407,0.0001503441,0.00907008],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1128634,"threshold_uncertainty_score":0.9997315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02973020496102218,"score_gpt":0.2746882769496241,"score_spread":0.2449580719886019,"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."}}