{"id":"W2937966487","doi":"10.3390/cancers11040507","title":"Integrative Analysis Reveals Subtype-Specific Regulatory Determinants in Triple Negative Breast Cancer","year":2019,"lang":"en","type":"article","venue":"Cancers","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Institute in Oncology and Hematology; University of Manitoba","funders":"Cure Brain Cancer Foundation; University of Manitoba; Natural Sciences and Engineering Research Council of Canada; CancerCare Manitoba Foundation","keywords":"microRNA; Biology; Transcription factor; Breast cancer; Gene; DNA methylation; Cancer research; Regulation of gene expression; Gene expression; Copy-number variation; Cancer; Computational biology; Genetics; Bioinformatics; Genome","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004881772,0.0002963739,0.0004545631,0.0004202784,0.0001529343,0.0003148315,0.000227879,0.0001151325,0.0006197778],"category_scores_gemma":[0.0006887094,0.0001098896,0.0005265559,0.0002939644,0.0001417958,0.0001259171,0.0002673472,0.0002006467,0.0000886408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002675093,"about_ca_system_score_gemma":0.000352803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004090418,"about_ca_topic_score_gemma":0.004541179,"domain_scores_codex":[0.9998391,0.00005092029,0.000005408888,0.00005684607,0.00002500455,0.00002269072],"domain_scores_gemma":[0.9998342,0.00006795386,0.00004684367,0.00001434727,0.00001889588,0.00001769193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001708005,0.0003999305,0.4546042,0.0002034455,0.0008603709,0.0009112917,0.0003325528,0.2939904,0.1250067,0.005739894,0.001709906,0.1145333],"study_design_scores_gemma":[0.00002395797,0.0001482458,0.1163275,0.00000840042,0.0001883828,0.0001951909,0.0001049922,0.873741,0.004635199,0.00355081,0.001055182,0.00002113139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9763095,0.0003441614,0.02206639,0.00008433369,0.000004459163,0.00001231414,0.0003798049,0.0001090091,0.0006902149],"genre_scores_gemma":[0.9960065,0.0001134124,0.002928369,0.00001979314,0.000005455133,0.00001224477,0.0005832561,0.00001527935,0.0003155882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004090418,"threshold_uncertainty_score":0.008133233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007210984743429606,"score_gpt":0.2421112645325459,"score_spread":0.2349002797891163,"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."}}