{"id":"W3014374922","doi":"10.1101/2020.04.03.023804","title":"Genomic evaluation of circulating proteins for drug target characterisation and precision medicine","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"National Health and Medical Research Council; Medical Research Council","keywords":"Mendelian randomization; Precision medicine; Computational biology; Disease; Biology; Quantitative trait locus; Drug; Gene; Genetics; Medicine; Bioinformatics; Pharmacology; Genetic variants; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004151524,0.0006347815,0.0008450976,0.002016787,0.0002389364,0.001562596,0.0004266601,0.0006001184,0.002933504],"category_scores_gemma":[0.007160117,0.0001795379,0.0005238641,0.002249269,0.0006151438,0.0004800759,0.0006965445,0.000858955,0.0005259308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004160633,"about_ca_system_score_gemma":0.0006146849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001007978,"about_ca_topic_score_gemma":0.0005548325,"domain_scores_codex":[0.9986196,0.0006312308,0.00008092436,0.0003260088,0.0002708992,0.00007135219],"domain_scores_gemma":[0.9953138,0.002480364,0.001024243,0.000636324,0.0003782328,0.0001671166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004484028,0.0003629471,0.4657808,0.001181567,0.002400448,0.001565097,0.0004755548,0.02263863,0.1959014,0.01637327,0.006085346,0.2827509],"study_design_scores_gemma":[0.0006816679,0.002104698,0.5545141,0.000316305,0.002919,0.003970304,0.0004408227,0.08153781,0.2426938,0.07440981,0.03623733,0.0001742691],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8039246,0.01043223,0.163529,0.002127966,0.000227981,0.0001311238,0.01389745,0.001070315,0.00465921],"genre_scores_gemma":[0.9593357,0.001430987,0.03583495,0.0002698502,0.0001151339,0.00004580084,0.002207236,0.00009238711,0.0006679273],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004151524,"threshold_uncertainty_score":0.02195561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02990503119309383,"score_gpt":0.2710374273001221,"score_spread":0.2411323961070282,"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."}}