{"id":"W2973477763","doi":"10.21926/obm.genet.1903094","title":"Introduction to Genetic Screening","year":2019,"lang":"en","type":"article","venue":"OBM Genetics","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Perspective (graphical); Field (mathematics); Engineering ethics; Data science; Computational biology; Computer science; Biology; Engineering; Artificial intelligence; Mathematics","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":[0.003818789,0.001683552,0.001084326,0.003638795,0.0009348637,0.003066832,0.001591149,0.004154979,0.02914263],"category_scores_gemma":[0.008593286,0.0008864935,0.001191354,0.001721877,0.002901399,0.003254717,0.00237484,0.009395878,0.02183509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001810023,"about_ca_system_score_gemma":0.001774706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001967704,"about_ca_topic_score_gemma":0.001563645,"domain_scores_codex":[0.9978899,0.0005768308,0.0002478843,0.0005040864,0.0006172367,0.0001640085],"domain_scores_gemma":[0.9928757,0.003846993,0.0002889753,0.0004640133,0.001840996,0.0006834194],"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":[0.0001603003,0.0001451839,0.0007305957,0.00169403,0.00004666784,0.0006283849,0.0002895138,0.0003578449,0.002547299,0.04849308,0.6109071,0.3340001],"study_design_scores_gemma":[0.00001086577,0.00004526049,0.0004390248,0.0004409165,0.000008595885,0.0009875147,0.00003863354,0.00007448152,0.000328417,0.01852197,0.979074,0.00003026361],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001711212,0.4297923,0.1135172,0.1780847,0.1639243,0.0005224583,0.003838665,0.003369353,0.1052399],"genre_scores_gemma":[0.0121772,0.4637893,0.07535499,0.1525537,0.156277,0.001027433,0.004313127,0.001382936,0.1331243],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02914263,"threshold_uncertainty_score":0.09749174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005678042389443491,"score_gpt":0.2264695134500616,"score_spread":0.2207914710606181,"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."}}