{"id":"W2896799578","doi":"10.1002/humu.23621","title":"Genetic database software as medical devices","year":2018,"lang":"en","type":"article","venue":"Human Mutation","topic":"Biomedical Ethics and Regulation","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Ontario Genomics","funders":"Canadian Institutes of Health Research; Government of Canada; Génome Québec; Ministère du Développement Économique, de l’Innovation et de l’Exportation; Genome Canada","keywords":"Software; Medical software; Context (archaeology); Harm; Computer science; Data science; Software development; Risk analysis (engineering); Biology; Software construction; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03790079,0.000786385,0.0007425287,0.005611917,0.004008928,0.01901122,0.004472835,0.01085881,0.008977831],"category_scores_gemma":[0.09763501,0.0009997698,0.001074458,0.003628059,0.02104719,0.01342277,0.008242145,0.005106423,0.004377756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006581748,"about_ca_system_score_gemma":0.01329488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009601577,"about_ca_topic_score_gemma":0.006814735,"domain_scores_codex":[0.9447049,0.02085089,0.006132134,0.003072247,0.02356407,0.001675695],"domain_scores_gemma":[0.8729256,0.08288427,0.006432489,0.01301016,0.02233584,0.002411647],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001588463,0.000013543,0.0006738359,0.0001009794,0.000004347815,0.0001766585,0.001349353,0.0004704576,0.0002840508,0.9570991,0.00879159,0.03102019],"study_design_scores_gemma":[0.00001847474,0.00003856934,0.0006537061,0.001123645,0.00002038837,0.0009826673,0.0009300496,0.00211063,0.001671624,0.3342949,0.6580857,0.00006958887],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01077461,0.01271106,0.3741909,0.09242339,0.002480802,0.000706262,0.0006060298,0.002084445,0.5040225],"genre_scores_gemma":[0.2747406,0.01603727,0.5612131,0.04624881,0.002915645,0.001302667,0.001074305,0.001701901,0.09476575],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9620992,"threshold_uncertainty_score":0.2004409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03320783064011153,"score_gpt":0.3645442307439514,"score_spread":0.3313364001038399,"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."}}