{"id":"W2065028684","doi":"10.1097/jto.0b013e3181fd83a4","title":"Prognostic and Predictive Value of Epidermal Growth Factor Receptor Tyrosine Kinase Domain Mutation Status and Gene Copy Number for Adjuvant Chemotherapy in Non-small Cell Lung Cancer","year":2010,"lang":"en","type":"article","venue":"Journal of Thoracic Oncology","topic":"Lung Cancer Treatments and Mutations","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research; Princess Margaret Cancer Centre; Queen's University; University Health Network","funders":"National Cancer Institute","keywords":"Medicine; Vinorelbine; Epidermal growth factor receptor; Oncology; Hazard ratio; Internal medicine; Chemotherapy; Lung cancer; Fluorescence in situ hybridization; Copy-number variation; Mutation; Cancer research; Cisplatin; Cancer; Confidence interval; Gene; Biology; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002280001,0.0001293911,0.0004660097,0.0001271521,0.00003783034,0.000007828039,0.00003524123,0.000133362,0.00005328535],"category_scores_gemma":[0.0001128291,0.00009818574,0.00005564585,0.00009630713,0.00009250352,0.0001040259,0.0000119187,0.0002326899,2.433143e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002258088,"about_ca_system_score_gemma":0.0005493242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001003986,"about_ca_topic_score_gemma":0.000081822,"domain_scores_codex":[0.9990468,0.000059963,0.0004313216,0.0001499255,0.0001137349,0.0001982503],"domain_scores_gemma":[0.9986727,0.0003053431,0.0004635435,0.0000638076,0.0003329373,0.0001617204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005705965,0.001034128,0.8537589,0.0006243038,0.0003663673,0.00009799662,0.008862526,0.00003535046,0.08971591,0.00003951617,0.0003434125,0.0394156],"study_design_scores_gemma":[0.01029882,0.003019719,0.9236854,0.0003047974,0.0009483221,0.0002725908,0.000762968,0.0007422761,0.05875707,0.0004260728,0.0006306467,0.0001513577],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946255,0.001001796,0.001697744,0.001209364,0.000399704,0.0008354753,0.0001644318,0.00000372834,0.00006227341],"genre_scores_gemma":[0.9690183,0.000622404,0.02985252,0.0001520012,0.0002151583,0.00005756124,0.00002369445,0.00002060553,0.00003769076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06992642,"threshold_uncertainty_score":0.4003899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00959289005364907,"score_gpt":0.3787633561425244,"score_spread":0.3691704660888753,"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."}}