{"id":"W2770958413","doi":"10.1159/000481682","title":"From the Data on Many, Precision Medicine for “One”: The Case for Widespread Genomic Data Sharing","year":2017,"lang":"en","type":"review","venue":"Biomedicine Hub","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Genomics","funders":"","keywords":"Interoperability; Data science; Context (archaeology); Precision medicine; Data sharing; Globe; Domain (mathematical analysis); Genomic medicine; Genomics; Health care; Computer science; Scale (ratio); Genome; Computational biology; Geography; World Wide Web; Medicine; Biology; Political science; Genetics; Cartography; Alternative medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["open_science"],"domain":null,"study_design":"theoretical_or_conceptual","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":["scholarly_communication","open_science"],"domain":null,"study_design":"theoretical_or_conceptual","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.005393961,0.0008074359,0.001474243,0.002904645,0.0008999244,0.003787154,0.002083455,0.003957737,0.004938615],"category_scores_gemma":[0.008306016,0.0003933003,0.0009036095,0.003988513,0.004168005,0.01008116,0.00322935,0.007693303,0.002669217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002594866,"about_ca_system_score_gemma":0.006742546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00183429,"about_ca_topic_score_gemma":0.00257911,"domain_scores_codex":[0.9978805,0.0008247696,0.000196584,0.0002175708,0.0007474109,0.0001331435],"domain_scores_gemma":[0.9919714,0.005676682,0.000394357,0.0004329241,0.001024911,0.000499767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006523839,0.00003548642,0.0003060561,0.01465298,0.0001725606,0.0004546327,0.0005009986,0.000439422,0.0004211125,0.08487401,0.09439691,0.8036807],"study_design_scores_gemma":[0.000004987091,0.00001453594,0.0001588855,0.00500142,0.00003051937,0.000758401,0.0002150115,0.00004451041,0.00008227204,0.01883007,0.9748438,0.00001571745],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001079467,0.9802846,0.0008499887,0.01541538,0.001007087,0.000006964624,0.00003262353,0.00001861082,0.002276717],"genre_scores_gemma":[0.001392571,0.9910499,0.0008728755,0.005153725,0.0009232609,0.00001436645,0.00004182951,0.000009907157,0.000541522],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9979165,"threshold_uncertainty_score":0.02852637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3301982220388213,"score_gpt":0.44965099735852,"score_spread":0.1194527753196988,"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."}}