{"id":"W2343780951","doi":"10.1158/1538-7445.am2015-1122","title":"Abstract 1122: Personalized oncogenomics in advanced stage breast cancer","year":2015,"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":"Canada's Michael Smith Genome Sciences Centre; BC Cancer Agency","funders":"","keywords":"Breast cancer; PTEN; Cancer; ARID1A; Oncology; Genomics; Personalized medicine; Biology; Internal medicine; Medicine; Cancer research; Bioinformatics; Gene; Genetics; Genome; Mutation; PI3K/AKT/mTOR pathway","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":[0.001210024,0.0002401267,0.0005171386,0.0006420834,0.0002231415,0.001071169,0.0003204498,0.0003895602,0.00315604],"category_scores_gemma":[0.00115406,0.000126543,0.0002165044,0.001080316,0.0002693276,0.000472539,0.0005488942,0.0004326743,0.0008960735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005569938,"about_ca_system_score_gemma":0.0006071392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004305985,"about_ca_topic_score_gemma":0.001056626,"domain_scores_codex":[0.9995686,0.000177727,0.00002258545,0.00007388273,0.0001205948,0.00003657195],"domain_scores_gemma":[0.9995341,0.0001661214,0.00009993804,0.00007578223,0.0000746845,0.00004930708],"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":[0.001579767,0.0002989236,0.09960648,0.001633216,0.0003022523,0.001605461,0.0003693461,0.006833508,0.1391477,0.004404678,0.03919801,0.7050206],"study_design_scores_gemma":[0.000412242,0.001594676,0.4693412,0.0007879337,0.0005907815,0.01256282,0.0007116378,0.02816447,0.1296032,0.03476841,0.3213181,0.0001444264],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.7256916,0.06611826,0.1194886,0.02024967,0.0006640987,0.0006662647,0.01828286,0.003937221,0.04490149],"genre_scores_gemma":[0.9081028,0.01696314,0.05658699,0.00275676,0.0007025067,0.0002108544,0.007905379,0.0003231437,0.006448535],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.00315604,"threshold_uncertainty_score":0.01055801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0689288528796059,"score_gpt":0.4033834826180395,"score_spread":0.3344546297384335,"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."}}