{"id":"W4205464551","doi":"10.1093/bib/bbac006","title":"Biomedical data, computational methods and tools for evaluating disease–disease associations","year":2022,"lang":"en","type":"review","venue":"Briefings in Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Training Program for Excellent Young Innovators of Changsha; National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Disease; Clinical phenotype; Computer science; Data science; Computational model; Complex disease; Perspective (graphical); Computational biology; Bioinformatics; Artificial intelligence; Medicine; Phenotype; Biology; Pathology; 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":[0.004680371,0.001583303,0.002411236,0.006995314,0.0003805108,0.002145507,0.001943511,0.001517566,0.004626885],"category_scores_gemma":[0.01194899,0.000569632,0.001761769,0.00795444,0.001072683,0.002611052,0.001233732,0.002243935,0.003263146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001118547,"about_ca_system_score_gemma":0.002855053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00295835,"about_ca_topic_score_gemma":0.002614131,"domain_scores_codex":[0.9978907,0.0007669629,0.0002999637,0.0003483236,0.0006306248,0.00006347607],"domain_scores_gemma":[0.9911464,0.007301016,0.0003434758,0.0002679742,0.0008329752,0.0001081594],"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":[0.00006435177,0.000069838,0.00157392,0.02508306,0.0005558233,0.0001928796,0.0001147085,0.002396096,0.0007989483,0.02009686,0.04149438,0.9075592],"study_design_scores_gemma":[0.00004509366,0.0001027322,0.00299135,0.01513264,0.0008158399,0.001578517,0.0001559147,0.004084799,0.001346413,0.05072132,0.9228633,0.000162055],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004123802,0.9709744,0.0202269,0.002589192,0.0007167505,0.00009745318,0.001235178,0.0002055805,0.003542193],"genre_scores_gemma":[0.003128231,0.9707347,0.02174009,0.001068199,0.0008563014,0.0001629883,0.001428571,0.00004169037,0.0008392603],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006995314,"threshold_uncertainty_score":0.02475244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.14733885691126,"score_gpt":0.4443573897455,"score_spread":0.2970185328342401,"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."}}