{"id":"W2983153415","doi":"10.1016/j.ccell.2019.10.003","title":"Companion Diagnostics to Identify Biomarkers of Response to Anticancer Drugs Targeting the Proteome","year":2019,"lang":"en","type":"letter","venue":"Cancer Cell","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Drug; Proteome; Companion diagnostic; Drug response; Drug discovery; Computational biology; Cancer research; Anticancer drug; Cancer drugs; Medicine; Pharmacology; Cancer; Bioinformatics; Biology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003277195,0.000799779,0.001085633,0.0006741433,0.0009066188,0.002611321,0.0009818116,0.01326191,0.003547324],"category_scores_gemma":[0.01025862,0.0004696361,0.0008153707,0.0003995548,0.002252928,0.002019736,0.0008614386,0.01529271,0.004357154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002241529,"about_ca_system_score_gemma":0.0009003454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006184422,"about_ca_topic_score_gemma":0.001253542,"domain_scores_codex":[0.9982094,0.0006373699,0.0001345749,0.0002129921,0.0006373517,0.0001683531],"domain_scores_gemma":[0.993145,0.004848455,0.0002303825,0.0002836365,0.001039769,0.0004528418],"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":[0.0007208805,0.0001833859,0.001311502,0.0005012614,0.00006949321,0.002787542,0.000113644,0.0003399037,0.01021332,0.01621639,0.857299,0.1102437],"study_design_scores_gemma":[0.0003997303,0.0003154052,0.001255694,0.0001814392,0.00005849848,0.00345383,0.0001291338,0.002740369,0.009549229,0.03587151,0.9459849,0.00006030371],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.003113474,0.02787385,0.00624419,0.8812268,0.07141273,0.0001334787,0.0003436907,0.0002463052,0.00940545],"genre_scores_gemma":[0.05791277,0.03041512,0.009770933,0.7176366,0.1473546,0.0005137981,0.0003368616,0.000116979,0.03594249],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.01326191,"threshold_uncertainty_score":0.01733166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01388931257298402,"score_gpt":0.3096122535292603,"score_spread":0.2957229409562762,"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."}}