{"id":"W2972508118","doi":"","title":"Biosimilars versus biologics for inflammatory conditions.","year":2019,"lang":"en","type":"article","venue":"PubMed","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Biosimilar; Medicine; Computer science; Data science; World Wide Web; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004263016,0.0001346131,0.0002201065,0.00007017266,0.00008294162,0.00001286333,0.0001839116,0.0003335435,0.0004765364],"category_scores_gemma":[0.0003304628,0.0001038428,0.0001428283,0.00009823156,0.0001792046,0.00004937735,0.00005432549,0.0001500373,0.0002103759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003160051,"about_ca_system_score_gemma":0.00001770996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.651782e-7,"about_ca_topic_score_gemma":0.000001883284,"domain_scores_codex":[0.9989608,0.00009087982,0.0002084211,0.0002726238,0.00002029995,0.0004470027],"domain_scores_gemma":[0.9989614,0.0006385943,0.00007273423,0.0002350074,0.0000576962,0.00003451269],"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":[0.00608333,0.00073581,0.06346492,0.0003159727,0.002226453,0.000008726242,0.000107315,0.00001078184,0.1603522,0.07459364,0.376485,0.3156158],"study_design_scores_gemma":[0.00411684,0.000213656,0.1047684,0.00000588507,0.0001059153,0.00000641255,0.00006615072,0.000006902049,0.06570495,0.001337051,0.8233269,0.0003409344],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9121644,0.004719532,0.0008231485,0.009547001,0.02731041,0.00718968,0.001018686,0.0006544522,0.03657266],"genre_scores_gemma":[0.9921293,0.00006046302,0.000616688,0.001352871,0.00008588335,0.001072257,0.0001109429,0.00001784078,0.004553699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4468418,"threshold_uncertainty_score":0.5217739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04090798055579421,"score_gpt":0.2743308272192981,"score_spread":0.2334228466635039,"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."}}