{"id":"W3039150496","doi":"10.3389/fgene.2020.00654","title":"Gene Set Analysis: Challenges, Opportunities, and Future Research","year":2020,"lang":"en","type":"review","venue":"Frontiers in Genetics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":224,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Set (abstract data type); Computer science; Strengths and weaknesses; Class (philosophy); Data set; Data mining; Data science; Computational biology; Biology; Artificial intelligence","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":[0.007686141,0.0008778283,0.002332519,0.003205104,0.0005507449,0.003124194,0.002359304,0.002335862,0.003769184],"category_scores_gemma":[0.007139469,0.0004061164,0.001067571,0.005103601,0.002470892,0.006234153,0.001564827,0.004417143,0.002403379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001965743,"about_ca_system_score_gemma":0.004307389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001885417,"about_ca_topic_score_gemma":0.003115232,"domain_scores_codex":[0.998828,0.0004193912,0.0001205315,0.00018448,0.0003573431,0.00009035084],"domain_scores_gemma":[0.9922566,0.00509975,0.000287391,0.0002213803,0.001760983,0.0003739294],"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":[0.00008180794,0.00007307866,0.0003878694,0.01265392,0.00009302528,0.0001668083,0.0001666115,0.0008802512,0.0006749328,0.03437529,0.0360644,0.9143821],"study_design_scores_gemma":[0.00003199008,0.0001020964,0.001203447,0.01342423,0.000150122,0.001346808,0.0004180332,0.00113656,0.0005089185,0.06838738,0.9132164,0.00007402873],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001043316,0.9944101,0.0009916356,0.003537513,0.0003764657,0.000004388383,0.00001994828,0.00001902623,0.0005366048],"genre_scores_gemma":[0.0009120131,0.9951319,0.001838177,0.001138468,0.0006305347,0.00001418633,0.00004707331,0.000009319221,0.00027835],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007686141,"threshold_uncertainty_score":0.0406487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1091931569587053,"score_gpt":0.3370184818457165,"score_spread":0.2278253248870112,"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."}}