{"id":"W2766114272","doi":"10.1186/s12885-017-3603-z","title":"Personalized treatment of women with early breast cancer: a risk-group specific cost-effectiveness analysis of adjuvant chemotherapy accounting for companion prognostic tests OncotypeDX and Adjuvant!Online","year":2017,"lang":"en","type":"article","venue":"BMC Cancer","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto General Hospital; University of Alberta","funders":"Universität Innsbruck; Medizinische Universität Innsbruck; Austrian Federal Ministry of Economy, Family and Youth; University of Toronto; Standortagentur Tirol; Bundesministerium für Verkehr, Innovation und Technologie; European Commission; University of Alberta; Huntsman Cancer Institute","keywords":"Medicine; Oncology; Breast cancer; Internal medicine; Surgical oncology; Cohort; Risk assessment; Cost effectiveness; Cancer; Risk analysis (engineering)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001410653,0.0002720497,0.000737936,0.00007627019,0.0001847599,0.00002666011,0.0001287202,0.00007580779,0.00001996256],"category_scores_gemma":[0.00001982244,0.0002040836,0.00014135,0.000125488,0.0002796177,0.00001252548,0.00004181317,0.00003172842,1.059982e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002876391,"about_ca_system_score_gemma":0.0001418067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004543016,"about_ca_topic_score_gemma":0.007459773,"domain_scores_codex":[0.9987969,0.00005849824,0.0002194691,0.0004732793,0.0001457979,0.0003060139],"domain_scores_gemma":[0.9986373,0.00009539379,0.0005605646,0.0003902997,0.0002444286,0.00007206947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003687735,0.0004011744,0.9297089,0.00009695649,0.003051192,6.639439e-7,0.0005911615,0.000140502,0.01027225,0.000004882114,0.000006867069,0.05203774],"study_design_scores_gemma":[0.006562529,0.0007115652,0.9864244,0.0001418392,0.001267593,0.000002638547,0.0001991657,0.0001838602,0.003591768,0.000004268789,0.0006975582,0.0002127699],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898652,0.006163762,0.0004823544,0.00004628495,0.00006500407,0.001035403,0.002326013,0.000008265368,0.000007669899],"genre_scores_gemma":[0.9933068,0.004706779,0.0004342723,0.000008958909,0.0001766651,0.001185842,0.0001233215,0.00003475419,0.00002263238],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05671557,"threshold_uncertainty_score":0.8322287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02376690480577787,"score_gpt":0.3178894248512075,"score_spread":0.2941225200454296,"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."}}