{"id":"W3014786823","doi":"10.3389/fgene.2020.00303","title":"Genomic Sequencing Capacity, Data Retention, and Personal Access to Raw Data in Europe","year":2020,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Université du Luxembourg","keywords":"Raw data; Exome; Exome sequencing; Reuse; Whole genome sequencing; Data access; Genome; Data science; World Wide Web; Computer science; Biology; Genetics; Database; Gene","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":[0.01758364,0.0001440371,0.0002335632,0.001304446,0.001473648,0.004524938,0.0008218384,0.001120619,0.002614178],"category_scores_gemma":[0.02730579,0.0002378846,0.0001853148,0.002688873,0.004798484,0.004353599,0.003506426,0.0008245988,0.0001835933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002610124,"about_ca_system_score_gemma":0.002897978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008740161,"about_ca_topic_score_gemma":0.003938262,"domain_scores_codex":[0.9889054,0.005998363,0.0008532326,0.001234117,0.001259112,0.001749686],"domain_scores_gemma":[0.9703161,0.01823828,0.005199749,0.00205931,0.001673978,0.002512617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005774549,0.0002564519,0.5162846,0.0005013275,0.000118016,0.003437287,0.1101012,0.006262546,0.004699086,0.1401087,0.006871689,0.2107816],"study_design_scores_gemma":[0.00005404182,0.0003755822,0.6044599,0.001966972,0.00008590663,0.004612771,0.1449257,0.002649433,0.005279669,0.05636941,0.178988,0.0002326822],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9734736,0.001978106,0.00257953,0.005642186,0.00003166744,0.00001171454,0.000115896,0.00002160395,0.01614568],"genre_scores_gemma":[0.9973751,0.0006325171,0.0007552189,0.0006106453,0.00001232285,0.000006878462,0.00005116421,0.000008800573,0.0005472546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01758364,"threshold_uncertainty_score":0.09299231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08295995818619488,"score_gpt":0.2832679623515345,"score_spread":0.2003080041653396,"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."}}