{"id":"W2983865285","doi":"10.3389/fgene.2019.01057","title":"Ensuring Best Practice in Genomic Education and Evaluation: A Program Logic Approach","year":2019,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Health and Medical Research Council; State Government of Victoria; University of Melbourne; Macquarie University; Murdoch Children's Research Institute; Medical Research Council; Children’s Hospital of Wisconsin Research Institute; University of Ottawa","keywords":"Process (computing); Computer science; Identification (biology); Genomics; Relevance (law); Logic model; Knowledge management; Process management; Data science; Engineering; Genome; Political science; Biology; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00321393,0.0001030392,0.0001759074,0.0002837689,0.0001288214,0.00001781614,0.0001523487,0.0001211475,0.00004962979],"category_scores_gemma":[0.0007925798,0.0001089703,0.00001051413,0.0004716287,0.0000464201,0.0001610892,0.00008343821,0.0003568177,0.00007198329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005285977,"about_ca_system_score_gemma":0.001644784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001631325,"about_ca_topic_score_gemma":0.00007517247,"domain_scores_codex":[0.997172,0.001092567,0.0005906698,0.0003400409,0.0003370663,0.0004676467],"domain_scores_gemma":[0.998867,0.0003218428,0.0002451212,0.0002712987,0.0001825736,0.0001122162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002287246,0.0002726228,0.802277,0.0002898508,0.000005066775,4.31723e-7,0.02460806,0.000654812,0.00006842714,0.0002019575,0.004257265,0.1673417],"study_design_scores_gemma":[0.003347316,0.0003477914,0.6172552,0.0002185764,0.00003750272,0.000009162314,0.0985532,0.04949298,0.00001167391,0.002189628,0.2281057,0.0004312604],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9711689,0.001359463,0.0006704361,0.002086271,0.001501102,0.004554539,0.00000449237,0.00002197198,0.01863284],"genre_scores_gemma":[0.6646122,0.0006286131,0.3280522,0.004542142,0.0001866225,0.001352261,0.00001711235,0.00002236069,0.0005864112],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3273818,"threshold_uncertainty_score":0.444368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.336052116352987,"score_gpt":0.6245930447612147,"score_spread":0.2885409284082276,"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."}}