{"id":"W2793992791","doi":"10.1038/sdata.2018.39","title":"Simplifying research access to genomics and health data with Library Cards","year":2018,"lang":"en","type":"article","venue":"Scientific Data","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Data science; Process (computing); Data access; Authentication (law); Protocol (science); Genomics; World Wide Web; Database; Biology; Genome; Medicine; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.03119317,0.0001081081,0.000258918,0.0003618741,0.000871663,0.001609054,0.005788297,0.0001122562,0.0002341542],"category_scores_gemma":[0.008252871,0.00008192217,0.000008931773,0.00159211,0.002251395,0.001347958,0.02614279,0.001362977,0.0002634318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006879942,"about_ca_system_score_gemma":0.004710132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003000945,"about_ca_topic_score_gemma":0.002043603,"domain_scores_codex":[0.9947011,0.0001932204,0.0003662191,0.00196017,0.002010239,0.0007690517],"domain_scores_gemma":[0.9840975,0.002119077,0.00006821797,0.01201487,0.0006272923,0.001073044],"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":[0.0001839278,0.00008941391,0.01196571,0.0003513689,0.00003211321,0.00002672151,0.0003807536,2.317519e-7,0.0002706525,0.0009073328,0.9557606,0.03003117],"study_design_scores_gemma":[0.0006993183,0.0007259244,0.02161297,0.0006726908,0.00001704294,0.00002885212,0.0005300752,0.001836342,0.0005610944,0.004941603,0.9681893,0.0001848072],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3701953,0.002954722,0.004492181,0.5299573,0.003992917,0.007285179,0.03656359,0.0004950446,0.04406376],"genre_scores_gemma":[0.7797031,0.001747862,0.1135633,0.01725888,0.004138965,0.00004514082,0.03381315,0.0002709184,0.04945862],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5126984,"threshold_uncertainty_score":0.9995909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.933510998259124,"score_gpt":0.7230294947196095,"score_spread":0.2104815035395144,"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."}}