{"id":"W2008233061","doi":"10.1016/j.ygeno.2013.04.007","title":"Clinical genomics information management software linking cancer genome sequence and clinical decisions","year":2013,"lang":"en","type":"article","venue":"Genomics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; Queen's University; University Health Network; University of Toronto; Ontario Institute for Cancer Research","funders":"Ontario Ministry of Research and Innovation; Ontario Ministry of Research, Innovation and Science; Princess Margaret Cancer Foundation; Cancer Care Ontario","keywords":"Genomics; Software; Personal genomics; Computer science; Process (computing); DNA sequencing; Data science; Biology; Bioinformatics; Computational biology; Genome; Genetics; Gene","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":[0.0004735202,0.0002152492,0.0002625045,0.00006124282,0.0001623,0.0001619063,0.0003364634,0.0002840788,0.00003487436],"category_scores_gemma":[0.0001792285,0.0002247244,0.0001543886,0.0000710227,0.0001626277,0.00002281007,0.0005838245,0.0002000448,0.0001231638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009518151,"about_ca_system_score_gemma":0.0002096173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008558133,"about_ca_topic_score_gemma":0.00008743683,"domain_scores_codex":[0.9982022,0.00004827802,0.0008465325,0.0004337475,0.0001144793,0.0003547459],"domain_scores_gemma":[0.9986845,0.0001125693,0.0002466971,0.0005414514,0.0001618212,0.0002529945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001363923,0.0001459987,0.1062452,0.00006879181,0.0004931524,0.000008807873,0.0001889008,0.002013186,0.00799393,0.0005029004,0.006568267,0.8756344],"study_design_scores_gemma":[0.001578667,0.0003056328,0.1440539,0.00003792128,0.0001411969,0.00002053649,0.0001767192,0.001020696,0.0002881603,0.001310011,0.8504093,0.000657208],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782726,0.00135742,0.01784939,0.0001908407,0.00106064,0.000624991,0.000209153,0.00002333839,0.000411687],"genre_scores_gemma":[0.6693409,0.1741313,0.1407253,0.01024128,0.002822286,0.0002732243,0.001576098,0.00012986,0.0007597457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8749772,"threshold_uncertainty_score":0.9163994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0312802503984551,"score_gpt":0.3242733391721115,"score_spread":0.2929930887736564,"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."}}