{"id":"W2919245049","doi":"10.3389/fgene.2019.00156","title":"Gene Expression-Based Predictive Markers for Paclitaxel Treatment in ER+ and ER− Breast Cancer","year":2019,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Calgary","funders":"National Natural Science Foundation of China","keywords":"Breast cancer; Paclitaxel; Gene expression profiling; Robustness (evolution); Gene expression; Oncology; Medicine; Gene; Computational biology; Bioinformatics; Cancer; Internal medicine; Biology; Genetics","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":[0.0007879742,0.0003515567,0.0006118273,0.001283972,0.0001854203,0.000589588,0.0003085524,0.0003241474,0.0004349198],"category_scores_gemma":[0.002489257,0.0001415546,0.0003926677,0.001552426,0.0002101807,0.0002558881,0.0002789763,0.0004849344,0.000183677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004502688,"about_ca_system_score_gemma":0.0004942366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001277342,"about_ca_topic_score_gemma":0.001698361,"domain_scores_codex":[0.9996862,0.00009147949,0.00002503903,0.00008192134,0.0000704402,0.00004490314],"domain_scores_gemma":[0.9992963,0.0003794344,0.0001459094,0.00005837782,0.00008896505,0.00003090012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002455343,0.0005435255,0.4896659,0.0003166582,0.000350353,0.0006121848,0.0001609053,0.1003749,0.1039258,0.001484512,0.003100093,0.2970097],"study_design_scores_gemma":[0.0001343002,0.0006757401,0.3729355,0.0000738476,0.0005586935,0.0007190302,0.0002785183,0.534668,0.07765989,0.006840281,0.005381352,0.00007485388],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9622307,0.002241241,0.03104902,0.0004296076,0.00003283762,0.00007698776,0.002158202,0.0004005552,0.001380919],"genre_scores_gemma":[0.9833629,0.0004401712,0.01366107,0.00006522799,0.00001657704,0.00004890641,0.002123483,0.00001580649,0.0002659266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001283972,"threshold_uncertainty_score":0.004167259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004190733116094815,"score_gpt":0.2156158958608465,"score_spread":0.2114251627447517,"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."}}