{"id":"W4393845458","doi":"10.5281/zenodo.5576255","title":"Activation level of 64 gene signatures in glioblastoma","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glioblastoma; Gene; Biology; Computational biology; Genetics; Cancer research","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":[0.0004518894,0.00127567,0.00110851,0.001517292,0.0004210588,0.0009780513,0.001188629,0.001169379,0.01814075],"category_scores_gemma":[0.001831786,0.0003764739,0.001241546,0.002020623,0.0002261878,0.0004444475,0.0008004534,0.0009314212,0.01862352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009891499,"about_ca_system_score_gemma":0.001029606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01016457,"about_ca_topic_score_gemma":0.01930787,"domain_scores_codex":[0.9995918,0.00004661522,0.00004524173,0.0001547995,0.00008913746,0.00007237266],"domain_scores_gemma":[0.9996164,0.0001221967,0.00005160882,0.00008538216,0.0000786102,0.00004577039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009868667,0.0001122954,0.01905475,0.002521899,0.000341976,0.0002535917,0.00006164818,0.003681364,0.003660045,0.0008882338,0.9454097,0.02302761],"study_design_scores_gemma":[0.001476765,0.0002353363,0.1047737,0.0008322528,0.0006010182,0.001507953,0.0002280014,0.009850797,0.0101758,0.006207374,0.8639709,0.0001399829],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005200365,0.0004533242,0.0003758695,0.0001060067,0.00003597717,0.00002283438,0.9917271,0.001072038,0.001006538],"genre_scores_gemma":[0.005447073,0.0001458027,0.0007581753,0.00007888157,0.000006229208,0.00007406478,0.9928145,0.00008761388,0.0005876766],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01814075,"threshold_uncertainty_score":0.06068689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03112011868020627,"score_gpt":0.2474681187923283,"score_spread":0.216348000112122,"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."}}