{"id":"W4399976754","doi":"10.1038/s41684-024-01395-2","title":"Model matchmaking via the Solve-RD Rare Disease Models & Mechanisms Network (RDMM-Europe)","year":2024,"lang":"en","type":"article","venue":"Lab Animal","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Hospital for Sick Children; University of Toronto","funders":"National Institute of Neurological Disorders and Stroke; Third Health Programme; Medical Research Council; European Commission","keywords":"Disease; Computer science; Computational biology; Rare disease; Intensive care medicine; Medicine; Biology; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001276782,0.0002147814,0.0001206253,0.00001934965,0.0002070219,0.0001548409,0.0003171191,0.00008484334,0.00003611543],"category_scores_gemma":[0.00001191612,0.0001570438,0.0001740171,0.0001102972,0.00004928857,0.000008731635,0.0002960325,0.0001196774,0.00005593051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001104126,"about_ca_system_score_gemma":0.00013243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009255367,"about_ca_topic_score_gemma":0.00002297337,"domain_scores_codex":[0.9987969,0.00003584863,0.0001763995,0.0004621575,0.0001517414,0.00037689],"domain_scores_gemma":[0.9992949,0.00001017992,0.00003546854,0.0004349959,0.00006179328,0.0001626318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001011405,0.0001926269,0.00009386176,0.0002508234,0.0004168948,0.0003388289,0.0003619783,0.2742058,0.5201743,0.1400486,0.06025731,0.002647617],"study_design_scores_gemma":[0.0004859513,0.0002564068,0.0003442365,0.000142091,0.0003332272,0.0000770254,0.00007620312,0.8043233,0.002698188,0.09030925,0.09988987,0.001064255],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6182587,0.0212856,0.3526862,0.001821891,0.0008013651,0.0005967844,0.0004266999,0.0001833438,0.003939422],"genre_scores_gemma":[0.9942402,0.0002861519,0.002014358,0.0009506397,0.0006167702,0.00003207195,0.0002255478,0.00006528598,0.001568946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5301175,"threshold_uncertainty_score":0.6404059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01906753083712667,"score_gpt":0.2421706987152525,"score_spread":0.2231031678781258,"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."}}