{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002521785,0.0003680387,0.0007375969,0.0001625139,0.0002675609,0.0002732603,0.000648035,0.0002579712,0.00001858823],"category_scores_gemma":[0.002905562,0.0003611816,0.000217824,0.0002182452,0.000117969,0.00004816494,0.001107618,0.0003116493,0.000002866743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008204728,"about_ca_system_score_gemma":0.000942536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004905863,"about_ca_topic_score_gemma":0.000001710515,"domain_scores_codex":[0.9974396,0.0001812133,0.00127225,0.0003954836,0.000321747,0.0003897139],"domain_scores_gemma":[0.9974009,0.0008474557,0.0007465969,0.000677101,0.00005813951,0.0002698568],"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":[0.00001281348,0.00004239703,0.000002250833,0.004226793,0.0001080419,4.924666e-7,0.00004945738,0.0001727463,1.121116e-7,0.0004881552,0.004452692,0.9904441],"study_design_scores_gemma":[0.0003726813,0.00006320832,0.00001519062,0.0004902062,0.0003472129,0.000006086395,0.00004354315,0.1497382,2.890139e-8,0.001005252,0.84755,0.0003683945],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000004113433,0.8428265,0.1504709,0.0001429532,0.0002690888,0.001456056,0.004639619,0.00002050787,0.0001702051],"genre_scores_gemma":[0.000001504473,0.6822358,0.267395,0.0006930993,0.0001663638,0.0002335147,0.04918836,0.00004356508,0.00004275823],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9900756,"threshold_uncertainty_score":0.999884,"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."}}