{"id":"W2912199505","doi":"10.1016/j.clgc.2019.01.015","title":"COMPARZ Post Hoc Analysis: Characterizing Pazopanib Responders With Advanced Renal Cell Carcinoma","year":2019,"lang":"en","type":"article","venue":"Clinical Genitourinary Cancer","topic":"Renal cell carcinoma treatment","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; University of British Columbia","funders":"Janssen Biotech; National Cancer Institute; Eisai; Ipsen Biopharmaceuticals; Prometheus; North Carolina GlaxoSmithKline Foundation; Novartis; GlaxoSmithKline Australia; Exelixis; Sanofi; GlaxoSmithKline; Merck; Astellas Pharma Global Development; Bayer Corporation; Bristol-Myers Squibb; AstraZeneca; Memorial Sloan-Kettering Cancer Center; Roche; Astellas Pharma US; Novartis Pharmaceuticals Corporation; Pfizer","keywords":"Pazopanib; Medicine; Post-hoc analysis; Oncology; Renal cell carcinoma; Internal medicine; Post hoc; Sunitinib","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":[0.009481032,0.0009075463,0.002206184,0.000645234,0.0003404242,0.0009075186,0.0008972966,0.000792584,0.008479861],"category_scores_gemma":[0.01061823,0.0002692103,0.00405864,0.0005953097,0.0006458081,0.000867974,0.0007151013,0.001341837,0.0005627611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007582306,"about_ca_system_score_gemma":0.000786789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004207873,"about_ca_topic_score_gemma":0.0005241023,"domain_scores_codex":[0.99042,0.006672503,0.0004861878,0.001241601,0.0007296284,0.0004500676],"domain_scores_gemma":[0.9876842,0.008446647,0.001602508,0.001294103,0.0006032397,0.0003692897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"observational","study_design_scores_codex":[0.843869,0.00373861,0.08471502,0.001163172,0.01846168,0.0004233302,0.0002503128,0.003265652,0.009111541,0.0004475554,0.005539122,0.02901503],"study_design_scores_gemma":[0.07541799,0.371635,0.4550195,0.0001315112,0.01918512,0.001462414,0.0006765891,0.02898439,0.02458484,0.002366314,0.02034227,0.0001940127],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904584,0.0009293997,0.002874045,0.000214404,0.0002375564,0.0009400396,0.002815533,0.0000971805,0.001433499],"genre_scores_gemma":[0.9906331,0.0001253247,0.00190643,0.0003552871,0.0001431114,0.001847744,0.003343541,0.00006868382,0.001576778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009481032,"threshold_uncertainty_score":0.0501411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03562386660572312,"score_gpt":0.3303050783745614,"score_spread":0.2946812117688382,"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."}}