{"id":"W4293105950","doi":"10.1002/ggn2.202200016","title":"GA4GH Phenopackets: A Practical Introduction","year":2022,"lang":"en","type":"article","venue":"Advanced Genetics","topic":"Ocular Oncology and Treatments","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Human Genome Research Institute; National Institutes of Health; Alan Turing Institute","keywords":"Suite; Schema (genetic algorithms); Disease; Medical diagnosis; Genomics; Computer science; Data science; Health care; Data sharing; Alliance; Clinical phenotype; Computational biology; Bioinformatics; Medicine; Phenotype; Genome; Biology; Information retrieval; Genetics; Pathology; Alternative medicine; Geography","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":[0.007722124,0.001786357,0.0009004445,0.003997593,0.001185927,0.006294097,0.004003463,0.003862074,0.1065933],"category_scores_gemma":[0.02277315,0.001858599,0.001588554,0.002791795,0.001649077,0.006718603,0.005140882,0.005670534,0.05384579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001365003,"about_ca_system_score_gemma":0.001774722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003054098,"about_ca_topic_score_gemma":0.00305444,"domain_scores_codex":[0.9970359,0.000941291,0.0003966954,0.0003811102,0.001098269,0.0001468015],"domain_scores_gemma":[0.9923084,0.003761766,0.0003178913,0.001297785,0.001674202,0.0006399562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003062994,0.0001373302,0.001842322,0.0004988985,0.00004702098,0.00185595,0.0006164306,0.003405906,0.00285691,0.09072709,0.6083924,0.2893136],"study_design_scores_gemma":[0.00004787006,0.00004549573,0.0005087533,0.0004278327,0.00001181675,0.002706497,0.000181874,0.004450054,0.00122836,0.05447421,0.9358429,0.00007431604],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001895595,0.002978185,0.8597841,0.01595042,0.003403055,0.001019346,0.0128491,0.0474242,0.05469606],"genre_scores_gemma":[0.01334008,0.005550748,0.8907413,0.008422963,0.001923936,0.001474373,0.01376658,0.01286285,0.05191715],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1065933,"threshold_uncertainty_score":0.35659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01636901947465111,"score_gpt":0.333818773909665,"score_spread":0.3174497544350139,"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."}}