{"id":"W2564719803","doi":"10.1038/gim.2016.189","title":"Public variant databases: liability?","year":2016,"lang":"en","type":"article","venue":"Genetics in Medicine","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Human Genome Research Institute; Canadian Institutes of Health Research; Government of Canada; Genome Canada","keywords":"Data sharing; Context (archaeology); Liability; Harm; Interpretation (philosophy); Corporate governance; Business; Medicine; Database; Political science; Computer science; Law; Alternative medicine; Biology; Accounting","routes":{"ca_aff":true,"ca_fund":true,"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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007983553,0.0001638774,0.0004622213,0.000268836,0.00004202074,0.000006940439,0.0003895034,0.0002379013,0.00247461],"category_scores_gemma":[0.06435106,0.00009210388,0.00005075143,0.0004998998,0.001102564,0.00005123539,0.0003123835,0.001019351,0.0002073398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000175559,"about_ca_system_score_gemma":0.0006072633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006255491,"about_ca_topic_score_gemma":0.0003724293,"domain_scores_codex":[0.9964663,0.0001802151,0.0007761024,0.0006156421,0.001394165,0.0005675396],"domain_scores_gemma":[0.988492,0.008733791,0.00008116219,0.00163491,0.0005465915,0.0005115051],"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":[0.0005224034,0.001307835,0.5336297,0.001063429,0.0001527917,0.001434695,0.0006622572,0.000002132603,0.03632286,0.2404407,0.01658217,0.167879],"study_design_scores_gemma":[0.02016454,0.004054848,0.24021,0.006148978,0.0001736828,0.0003107311,0.0005384072,0.0004641204,0.004067367,0.2995841,0.4235573,0.0007259251],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2775797,0.004663155,0.03678205,0.5685277,0.001960047,0.001857167,0.0000556136,0.000207584,0.108367],"genre_scores_gemma":[0.9725531,0.008099797,0.008247855,0.003741617,0.00102311,0.00004228237,0.00002022028,0.00004217491,0.006229791],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6949734,"threshold_uncertainty_score":0.9984373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.700265549801828,"score_gpt":0.5842779702308315,"score_spread":0.1159875795709965,"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."}}