{"id":"W4380485664","doi":"10.3390/cancers15123158","title":"Integrating Multi-Omics Analysis for Enhanced Diagnosis and Treatment of Glioblastoma: A Comprehensive Data-Driven Approach","year":2023,"lang":"en","type":"article","venue":"Cancers","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"CancerCare Manitoba; Research Institute in Oncology and Hematology; Children's Hospital Research Institute of Manitoba; University of Manitoba","funders":"Fundação para a Ciência e a Tecnologia; Rede de Química e Tecnologia; Canadian Institutes of Health Research; Laboratório Associado para a Química Verde; European Commission","keywords":"Glioblastoma; Gene; microRNA; Temozolomide; Disease; Cancer research; Medicine; Computational biology; Bioinformatics; Biology; Internal medicine; Genetics","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":[0.003780406,0.001615803,0.00215628,0.006176536,0.0008364904,0.00325272,0.001041106,0.0007094111,0.0008118922],"category_scores_gemma":[0.003692792,0.0005278146,0.003494305,0.003784686,0.0004790725,0.001626938,0.002761521,0.001252618,0.0005993525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001336823,"about_ca_system_score_gemma":0.003383405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003930773,"about_ca_topic_score_gemma":0.007629281,"domain_scores_codex":[0.9984244,0.0004556432,0.0001529041,0.0004037672,0.0004481122,0.0001151379],"domain_scores_gemma":[0.9982121,0.0006293582,0.0002206823,0.0002049958,0.0005464013,0.0001864423],"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":[0.001493629,0.0008287102,0.07578547,0.00767567,0.004941117,0.002048949,0.001069883,0.1149734,0.1851049,0.01337158,0.02827161,0.5644352],"study_design_scores_gemma":[0.0001410765,0.0006865602,0.04461538,0.001158828,0.003275702,0.001197099,0.001499258,0.7338656,0.05437591,0.08562449,0.07319879,0.0003613415],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08230443,0.02567995,0.8357645,0.006276993,0.0003438765,0.0009926722,0.03615364,0.008836013,0.003647992],"genre_scores_gemma":[0.2639412,0.01502637,0.659197,0.001767451,0.0003817204,0.0008271135,0.05680377,0.0007722658,0.001283076],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006176536,"threshold_uncertainty_score":0.01999295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04312370533409424,"score_gpt":0.2977176361499548,"score_spread":0.2545939308158606,"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."}}