{"id":"W2338990367","doi":"10.1093/jlb/lsw018","title":"Precision medicine: drowning in a regulatory soup?","year":2016,"lang":"en","type":"article","venue":"Journal of Law and the Biosciences","topic":"Injury Epidemiology and Prevention","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Precision medicine; Medicine; Computational biology; Biology; Pathology","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":[0.1418317,0.001710754,0.002875001,0.002783423,0.01661919,0.03841534,0.0071554,0.05648058,0.01075518],"category_scores_gemma":[0.1831106,0.001512924,0.00317485,0.00320474,0.06038006,0.05874646,0.01184074,0.09022361,0.005422362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01459688,"about_ca_system_score_gemma":0.04375066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01993211,"about_ca_topic_score_gemma":0.01471103,"domain_scores_codex":[0.8753248,0.06220169,0.006231046,0.01554169,0.03216131,0.008539435],"domain_scores_gemma":[0.852718,0.09630538,0.005448096,0.01035632,0.02532683,0.009845321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006403129,0.00006497938,0.0002865718,0.0002539314,0.00003880617,0.0001854235,0.003263375,0.0002008963,0.0003874991,0.593774,0.3698839,0.03159668],"study_design_scores_gemma":[0.00007225639,0.00009529679,0.0002463971,0.001298184,0.0000388673,0.0002935835,0.003322536,0.0004037431,0.0004519377,0.2544558,0.7391886,0.0001328546],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0003330706,0.01027444,0.003940064,0.9703639,0.008181264,0.00002071783,0.00003130895,0.00008935871,0.006765876],"genre_scores_gemma":[0.02109112,0.01021319,0.006393155,0.9452934,0.008639052,0.0001618142,0.00007738735,0.0001968222,0.007934046],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1418317,"threshold_uncertainty_score":0.7500865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02466899966330682,"score_gpt":0.3315446195904623,"score_spread":0.3068756199271555,"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."}}