{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002335996,0.00006664894,0.00009238238,0.00007233507,0.0001432307,0.00001410637,0.00005346713,0.0001591783,0.00290095],"category_scores_gemma":[0.0001874433,0.00005237895,0.00002775427,0.0001157399,0.0005035938,0.00005079958,0.00002519544,0.0001443752,0.0003695409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002305276,"about_ca_system_score_gemma":0.0001448693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007344696,"about_ca_topic_score_gemma":0.0001469988,"domain_scores_codex":[0.9989159,0.00003060239,0.0001842146,0.000169973,0.0005841397,0.0001151508],"domain_scores_gemma":[0.999429,0.00003334941,0.00005272163,0.0001520317,0.0001511828,0.0001816483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002694589,0.0008301417,0.02043622,0.001231958,0.000239981,0.0008877458,0.005717607,0.000003415047,0.02137632,0.039797,0.01707868,0.8921314],"study_design_scores_gemma":[0.003384126,0.001379895,0.9246252,0.0007542176,0.0002168643,0.0005549554,0.0002758993,0.004911341,0.00321267,0.02502513,0.03531596,0.0003437793],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785951,0.0001913026,0.0135853,0.004986494,0.0002427515,0.0001999399,0.000003412806,0.0001141277,0.002081546],"genre_scores_gemma":[0.9930778,0.0000100931,0.003278197,0.002124529,0.0008378452,0.000006038409,0.000235157,0.0000119927,0.0004183324],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9041889,"threshold_uncertainty_score":0.9980105,"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."}}