{"id":"W2497554238","doi":"10.1017/cbo9781107337459.020","title":"Signaling network analysis of genomic alterations predicts breast cancer drug targets","year":2015,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Breast cancer; Biology; Cancer; Genome; Computational biology; Genomics; Genome instability; Genetics; Gene; DNA; DNA damage","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":[0.0002600917,0.0005286071,0.0003577629,0.001816526,0.0001993902,0.0007929293,0.0002731645,0.0002955795,0.00426743],"category_scores_gemma":[0.0007519384,0.0002173381,0.0006841257,0.001558872,0.0001625139,0.0005319836,0.000307883,0.0004424531,0.00140813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000592132,"about_ca_system_score_gemma":0.0002794797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002260322,"about_ca_topic_score_gemma":0.004307861,"domain_scores_codex":[0.9998926,0.00001828696,0.000006766872,0.00003834593,0.00003264716,0.00001129201],"domain_scores_gemma":[0.9997817,0.000130741,0.00003490864,0.00001223395,0.00002701951,0.00001345024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006187738,0.0002218141,0.08183716,0.001388889,0.0007617219,0.0008928546,0.0002291082,0.1139946,0.08944701,0.04197429,0.06629612,0.6023377],"study_design_scores_gemma":[0.00005451994,0.0001902136,0.1241277,0.000329191,0.0005940445,0.001314714,0.0002736538,0.6058567,0.02988525,0.1276464,0.1096228,0.0001049417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5109437,0.06539818,0.285512,0.008253761,0.0005298029,0.0001853051,0.05862762,0.005272009,0.06527768],"genre_scores_gemma":[0.811235,0.03102395,0.1013799,0.0006662369,0.0003009792,0.0001294063,0.03702753,0.0003373633,0.01789987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00426743,"threshold_uncertainty_score":0.01427597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01250990443760441,"score_gpt":0.2007635457253099,"score_spread":0.1882536412877054,"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."}}