{"id":"W4308074043","doi":"10.1016/j.ajhg.2022.10.002","title":"Care4Rare Canada: Outcomes from a decade of network science for rare disease gene discovery","year":2022,"lang":"en","type":"review","venue":"The American Journal of Human Genetics","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Alberta Children's Hospital; University of Calgary; Children's Hospital of Eastern Ontario; University of Ottawa","funders":"Institute of Genetics; Genome Canada","keywords":"Exome sequencing; Data sharing; Exome; Leverage (statistics); Data science; Genome; Disease; Computational biology; Biology; Medicine; Gene; Genetics; Computer science; Alternative medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.009939764,0.001480053,0.002408797,0.004564447,0.001220093,0.004121617,0.002822479,0.003509067,0.01081641],"category_scores_gemma":[0.01860468,0.0004641106,0.001228078,0.006128082,0.002300834,0.002032215,0.002634225,0.004993736,0.003483543],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0215192,"about_ca_system_score_gemma":0.06722698,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3241895,"about_ca_topic_score_gemma":0.4794461,"domain_scores_codex":[0.997413,0.0004873756,0.0001645601,0.0002322819,0.00127528,0.0004275061],"domain_scores_gemma":[0.9799197,0.006411269,0.0008027224,0.0003775617,0.00909917,0.003389626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001839013,0.00003498605,0.0003234635,0.005510563,0.0001593179,0.0001351883,0.0000633868,0.0003271895,0.000157477,0.008584567,0.5169702,0.4675497],"study_design_scores_gemma":[0.00008165421,0.00003766922,0.0008737912,0.005674105,0.0001456523,0.00018117,0.00005052239,0.00008313092,0.00006696839,0.001843315,0.9909349,0.00002707882],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00009972411,0.9791101,0.000331836,0.01385774,0.003391184,0.0000211049,0.0003420608,0.00005805296,0.002788186],"genre_scores_gemma":[0.001028884,0.9857297,0.0007860207,0.007886903,0.001876148,0.0000248301,0.0004924152,0.00002295402,0.002152234],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9784808,"threshold_uncertainty_score":0.6446051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02754540138699885,"score_gpt":0.3066848362289532,"score_spread":0.2791394348419543,"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."}}