{"id":"W2160197082","doi":"10.1021/pr4001527","title":"Genome Wide Proteomics of ERBB2 and EGFR and Other Oncogenic Pathways in Inflammatory Breast Cancer","year":2013,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"14-3-3 protein interactions","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; George & Fay Yee Centre for Healthcare Innovation","funders":"National Institute of Environmental Health Sciences; National Cancer Institute; National Center for Research Resources; National Institute on Drug Abuse; National Institutes of Health","keywords":"Oncogene; SKBR3; Biology; Proteomics; ErbB; Transcriptome; Signal transduction; Cancer research; Computational biology; Cancer; Genetics; Bioinformatics; Gene; Breast cancer; Cell cycle; Gene expression","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":[0.001088148,0.0001030212,0.0001888741,0.0002579053,0.00005150872,0.00004695886,0.0001885376,0.0001333868,0.0001123832],"category_scores_gemma":[0.0002116271,0.00008571389,0.00005069051,0.000130738,0.0002084319,0.00002552506,0.0001748904,0.0004662394,0.000005593985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007430814,"about_ca_system_score_gemma":0.0003367797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002290173,"about_ca_topic_score_gemma":0.00005495567,"domain_scores_codex":[0.998656,0.00019869,0.0004081902,0.0001701528,0.0002964803,0.0002704276],"domain_scores_gemma":[0.9988993,0.00003684536,0.0002121661,0.0001802586,0.0005361811,0.0001351909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001618745,0.0000529393,0.04882067,0.00009455574,0.00005179368,0.000006572602,0.0001421299,0.000009829364,0.9497432,0.00001271461,0.0000753368,0.0008283531],"study_design_scores_gemma":[0.001852691,0.001012108,0.3996203,0.0003478642,0.00001292545,0.000567138,0.0005180609,0.000055588,0.5892885,0.001215933,0.005249564,0.0002592973],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968222,0.001444141,0.00008194488,0.0006243658,0.00002745331,0.0008712676,0.00001664887,0.000001365584,0.0001105796],"genre_scores_gemma":[0.9975685,0.0005951017,0.001226942,0.00002918587,0.0001887162,0.0001704959,7.105017e-7,0.00002344069,0.0001969431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3604547,"threshold_uncertainty_score":0.3495311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03046848294860334,"score_gpt":0.3291761056212428,"score_spread":0.2987076226726395,"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."}}