{"id":"W2316080597","doi":"10.1158/1538-7445.am2012-sy16-01","title":"Abstract SY16-01: Clinical trial design to match patients to treatment based on molecular profiling of tumors","year":2012,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Ontario Institute for Cancer Research","funders":"","keywords":"Druggability; Crizotinib; Personalized medicine; Precision medicine; Medicine; Clinical trial; Lung cancer; Cancer; Vemurafenib; Bioinformatics; Computational biology; Cancer research; Biology; Oncology; Genetics; Internal medicine; Gene; Pathology","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":[0.008940696,0.00146126,0.002835309,0.0007720606,0.0003711953,0.001145164,0.0006341101,0.00179261,0.01513241],"category_scores_gemma":[0.007004429,0.0005209253,0.001782053,0.0005623467,0.001295169,0.001425286,0.000766871,0.002110321,0.002290095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007984557,"about_ca_system_score_gemma":0.001834633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001810614,"about_ca_topic_score_gemma":0.00040804,"domain_scores_codex":[0.9962213,0.002814311,0.0002261552,0.0003432801,0.0001585425,0.0002364371],"domain_scores_gemma":[0.9974125,0.0009097488,0.00066874,0.000251244,0.0001643817,0.0005933507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"not_applicable","study_design_scores_codex":[0.9404359,0.003202056,0.002807295,0.0008569105,0.0009618984,0.00005408983,0.00006353338,0.002405622,0.004676324,0.001231247,0.002504124,0.04080098],"study_design_scores_gemma":[0.7674549,0.2043024,0.007038509,0.000172674,0.0007917665,0.000123585,0.00005394983,0.006700683,0.001497059,0.003372984,0.008437085,0.00005446472],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"protocol","genre_scores_codex":[0.9094555,0.007014475,0.009261011,0.003275991,0.00230307,0.05077372,0.004258588,0.0005064814,0.01315106],"genre_scores_gemma":[0.9058542,0.001574024,0.01351013,0.002436644,0.0006845588,0.06598225,0.002822577,0.00009050622,0.00704509],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.01513241,"threshold_uncertainty_score":0.050623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1543137797321397,"score_gpt":0.4588853082531105,"score_spread":0.3045715285209709,"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."}}