{"id":"W2943442365","doi":"10.1002/dta.2609","title":"Rapid characterization of structural and functional similarity for a candidate bevacizumab (Avastin) biosimilar using a multipronged mass‐spectrometry‐based approach","year":2019,"lang":"en","type":"article","venue":"Drug Testing and Analysis","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Apotex (Canada); IONICS Mass Spectrometry (Canada); York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biosimilar; Hydrogen–deuterium exchange; Chemistry; Mass spectrometry; Drug development; Bevacizumab; Small molecule; Tandem mass spectrometry; Computational biology; Drug; Pharmacology; Chromatography; Medicine; Biochemistry; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007323313,0.00031358,0.000284566,0.000884713,0.0002387321,0.0004942807,0.0002771362,0.0005227679,0.0008911323],"category_scores_gemma":[0.001105628,0.0001309939,0.0002508594,0.0003077953,0.0003465122,0.000444913,0.0003335207,0.0005913593,0.0002827702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003000906,"about_ca_system_score_gemma":0.0002782463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005377139,"about_ca_topic_score_gemma":0.0006752126,"domain_scores_codex":[0.9995341,0.00006133322,0.00002800939,0.0001038647,0.0002369895,0.00003567471],"domain_scores_gemma":[0.9993049,0.0001640178,0.0002539125,0.00005843018,0.0001486628,0.0000700971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008137072,0.00002283238,0.0009198934,0.00001703594,0.000009428475,0.00002322035,0.00002910294,0.0000980763,0.9961311,0.00007895163,0.00002226733,0.002566795],"study_design_scores_gemma":[0.00001078022,0.0004318765,0.01174268,0.000004336999,0.00002695737,0.0005847977,0.0000779004,0.004796603,0.9808171,0.0001181392,0.001372899,0.0000158786],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9631355,0.0006909503,0.03394128,0.0000966763,0.00002580434,0.00008652381,0.0004581001,0.0001583451,0.001406744],"genre_scores_gemma":[0.9750004,0.0002671593,0.02289785,0.00009670095,0.0000124811,0.0000395197,0.0004815679,0.00003668573,0.001167734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008911323,"threshold_uncertainty_score":0.003872991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04236129727187413,"score_gpt":0.2862754239209636,"score_spread":0.2439141266490894,"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."}}