{"id":"W2888172121","doi":"10.1016/j.atherosclerosis.2018.06.911","title":"Effect of an RNAi therapeutic targeting PCSK9 on atherogenic lipoproteins: Pre-specified secondary endpoints in orion 1","year":2018,"lang":"en","type":"article","venue":"Atherosclerosis","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"","keywords":"PCSK9; RNA interference; Monoclonal antibody; Messenger RNA; Pharmacology; Cholesterol; Chemistry; LDL receptor; Biology; Medicine; RNA; Antibody; Internal medicine; Gene; Immunology; Lipoprotein; Biochemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.00212874,0.0003005981,0.0003983117,0.0002106095,0.000124983,0.0001062069,0.001048253,0.0001222188,0.0001254819],"category_scores_gemma":[0.0001652333,0.000239655,0.0001404361,0.0007475775,0.0001257702,0.0006442809,0.0002337616,0.0002601941,0.00006664192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001251003,"about_ca_system_score_gemma":0.0001094201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001008676,"about_ca_topic_score_gemma":0.00005638507,"domain_scores_codex":[0.9966738,0.001198178,0.0005136483,0.0007026269,0.0005049958,0.0004067417],"domain_scores_gemma":[0.9980233,0.0007345848,0.00025022,0.000809688,0.00008290457,0.00009934342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001144158,0.0006506168,0.001173584,0.0001048762,0.0000897312,0.000006330149,0.005798025,0.001866664,0.1473108,0.004786531,0.00004023864,0.8370284],"study_design_scores_gemma":[0.002420324,0.006714131,0.1392258,0.0003147426,0.0000191054,0.000006848017,0.00004212993,0.0643832,0.7817616,0.004165188,0.0003808206,0.0005660961],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.967403,0.00008852929,0.03094792,0.00007310529,0.0004056286,0.000557923,0.000006521987,0.0001226793,0.0003947255],"genre_scores_gemma":[0.9845584,0.00001632199,0.01486098,0.0002290079,0.0001708818,0.00006789812,0.000004416495,0.00003956905,0.00005250469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8364624,"threshold_uncertainty_score":0.9772848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01931278934196265,"score_gpt":0.3019547380030363,"score_spread":0.2826419486610737,"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."}}