{"id":"W3006483941","doi":"10.5731/pdajpst.2019.010173","title":"A Semiquantitative Risk Assessment Methodology Fit for Biopharmaceutical Life Cycle Stages","year":2020,"lang":"en","type":"review","venue":"PDA Journal of Pharmaceutical Science and Technology","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alphora Research (Canada); Apotex (Canada); Sanofi (Canada)","funders":"","keywords":"Risk analysis (engineering); Risk assessment; Computer science; Risk management; Process (computing); Product (mathematics); Quality (philosophy); Biopharmaceutical; New product development; Process management; Engineering; Medicine; Business; Biotechnology","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":[0.01825811,0.002625931,0.001351793,0.008189447,0.0006702477,0.003345878,0.002731849,0.001634676,0.006248003],"category_scores_gemma":[0.03326007,0.0008518906,0.003511852,0.004009307,0.001557684,0.00318832,0.002311263,0.003058068,0.002655279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002690455,"about_ca_system_score_gemma":0.004376145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00175462,"about_ca_topic_score_gemma":0.00186776,"domain_scores_codex":[0.984947,0.006889431,0.001482804,0.001234945,0.005219718,0.0002261295],"domain_scores_gemma":[0.9720654,0.01569551,0.003117839,0.002554896,0.006347373,0.000218948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000263629,0.0002255977,0.005073098,0.01227961,0.0007543102,0.0002723999,0.0009104109,0.06438288,0.01107621,0.1460658,0.01720783,0.7414882],"study_design_scores_gemma":[0.0001533871,0.001174917,0.006527091,0.005186648,0.0008145561,0.001902823,0.0008412104,0.155672,0.031916,0.3094119,0.4858504,0.0005490779],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.001826995,0.01095824,0.976548,0.0005322136,0.0002299728,0.001049764,0.0008359204,0.0008840875,0.007134755],"genre_scores_gemma":[0.06371211,0.01043764,0.9147244,0.0005681523,0.000193504,0.003745419,0.001479666,0.0004246172,0.00471461],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01825811,"threshold_uncertainty_score":0.09655929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2653531718072619,"score_gpt":0.5447340979934341,"score_spread":0.2793809261861722,"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."}}