{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002229492,0.0001485866,0.0001756767,0.0000626285,0.00003653772,0.00009689305,0.001203593,0.00009218819,0.000004623962],"category_scores_gemma":[0.0004282317,0.0001769451,0.00001194963,0.0002357868,0.00006580599,0.00001245962,0.002699158,0.0001254535,0.000002763935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004017774,"about_ca_system_score_gemma":0.0002040258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008507047,"about_ca_topic_score_gemma":0.0004712196,"domain_scores_codex":[0.9985732,0.00004692959,0.000256738,0.0007599721,0.000107496,0.0002556973],"domain_scores_gemma":[0.9988797,0.00001101686,0.00005437155,0.0008494235,0.00004730136,0.0001581583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001778734,0.00004318914,0.7321134,0.0001008273,0.00006354438,0.00003865243,0.0007799809,0.003010588,0.1162764,0.00001133328,0.1374287,0.00995554],"study_design_scores_gemma":[0.003478341,0.0006237989,0.3093685,0.0001090467,0.000121755,0.00003616666,0.001011571,0.1434885,0.01799254,0.0002218286,0.5219096,0.001638416],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9777547,0.004499502,0.0150204,0.001187766,0.0004290112,0.0003034559,0.0006652314,0.000005919688,0.0001340556],"genre_scores_gemma":[0.9662919,0.005511584,0.02343969,0.002884739,0.0004499784,0.000006726892,0.00134389,0.00004331039,0.00002817007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4227449,"threshold_uncertainty_score":0.7215611,"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."}}