{"id":"W2977235223","doi":"10.1016/j.omtn.2019.09.019","title":"Computational Methods for Identifying Similar Diseases","year":2019,"lang":"en","type":"review","venue":"Molecular Therapy — Nucleic Acids","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":121,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China; Heilongjiang Postdoctoral Science Foundation","keywords":"Similarity (geometry); Pairwise comparison; Disease; Computational biology; Identification (biology); Phenotype; Benchmark (surveying); Function (biology); Bioinformatics; Biology; Computer science; Medicine; Artificial intelligence; Genetics; Gene; Pathology","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":[0.0003854398,0.0005869145,0.001100423,0.0001090423,0.0001370281,0.000129956,0.0006368038,0.0005851616,0.00004060009],"category_scores_gemma":[0.00003535112,0.0005179976,0.001234261,0.0001425697,0.00008522545,0.000006095882,0.0002014567,0.0002160512,0.00004811662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004013536,"about_ca_system_score_gemma":0.0002569845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.266251e-7,"about_ca_topic_score_gemma":1.555187e-7,"domain_scores_codex":[0.9978625,0.0002263902,0.0006689466,0.0006263327,0.0001688974,0.0004468907],"domain_scores_gemma":[0.9985227,0.00007740471,0.0003988334,0.0007538922,0.0001102659,0.0001369019],"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":[0.00003109263,0.00004672934,7.657419e-7,0.002407292,0.0007849624,0.000002078016,0.0000169991,0.0002371719,0.0002496536,0.0003587084,0.001571336,0.9942932],"study_design_scores_gemma":[0.0006015887,0.0001847463,0.000001051954,0.0005394531,0.0003902456,0.00001981176,0.00000744477,0.0008327121,0.00009363346,0.0014756,0.995242,0.0006116906],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000009221951,0.6632212,0.3350606,0.00001608188,0.0003664641,0.00103388,0.0001407719,0.00001948397,0.0001322558],"genre_scores_gemma":[0.00001883108,0.9269107,0.06830916,0.0006709312,0.0003277518,0.0002051437,0.003050636,0.0001756731,0.0003311643],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9936816,"threshold_uncertainty_score":0.9997272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05133603354306864,"score_gpt":0.3856518859271522,"score_spread":0.3343158523840835,"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."}}