{"id":"W3124855862","doi":"10.25916/sut.26244503","title":"Precision medicine: drowning in a regulatory soup?","year":2024,"lang":"en","type":"article","venue":"Own your potential (DEAKIN)","topic":"Biomedical Ethics and Regulation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Australian Research Council","keywords":"Precision medicine; Pharmacogenomics; Biobank; Personalized medicine; Confusion; Health care; Healthcare industry; Risk analysis (engineering); Regulatory science; Business; Medicine; Political science; Law; Bioinformatics; Psychology; Biology; Pharmacology","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":[0.1482582,0.00180273,0.002910249,0.002695311,0.01703677,0.03911472,0.007575743,0.0608895,0.01110039],"category_scores_gemma":[0.1845136,0.001578929,0.003464202,0.002963012,0.0598096,0.05994124,0.01237226,0.09471644,0.005897978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01443594,"about_ca_system_score_gemma":0.04326753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01888834,"about_ca_topic_score_gemma":0.01309364,"domain_scores_codex":[0.8700835,0.06701592,0.006295303,0.01558111,0.03157143,0.009452722],"domain_scores_gemma":[0.8546757,0.09470838,0.005390628,0.01037189,0.02446682,0.01038663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007068626,0.0000735032,0.0002878556,0.0002781327,0.00004172434,0.0002150418,0.003892258,0.0002188885,0.0004676728,0.5765571,0.3864993,0.03139793],"study_design_scores_gemma":[0.00007784415,0.00009915957,0.0002407362,0.001281861,0.0000410364,0.0002981192,0.003659761,0.0003947396,0.0005081453,0.2421275,0.7511323,0.000138727],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0003469295,0.009685379,0.003726417,0.9713409,0.008155697,0.00002096989,0.00003077445,0.00009112588,0.006601751],"genre_scores_gemma":[0.02158516,0.009100839,0.005747696,0.9475197,0.007782219,0.0001622491,0.00007039393,0.0001970673,0.007834688],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1482582,"threshold_uncertainty_score":0.7840735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02118375682322231,"score_gpt":0.3165284606024705,"score_spread":0.2953447037792482,"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."}}