{"id":"W3156859909","doi":"10.1016/j.ejca.2021.03.013","title":"The European Union and personalised cancer medicine","year":2021,"lang":"en","type":"article","venue":"European Journal of Cancer","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"European union; Limiting; Cancer; Precision medicine; Personalized medicine; Medicine; Risk analysis (engineering); Political science; Bioinformatics; Business; Pathology; Biology; Economic policy; Internal medicine; Engineering","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":[0.005822454,0.000255594,0.0005892492,0.001062923,0.0009433028,0.003965024,0.0005912309,0.005579581,0.01252312],"category_scores_gemma":[0.006944608,0.0001489187,0.0004185014,0.001351594,0.004406484,0.00336939,0.003996721,0.003480175,0.001433611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002501273,"about_ca_system_score_gemma":0.003211681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001974063,"about_ca_topic_score_gemma":0.001944141,"domain_scores_codex":[0.9968266,0.001742908,0.0001837334,0.0003537078,0.0005604249,0.0003326994],"domain_scores_gemma":[0.9970951,0.001316927,0.0004066334,0.0004008554,0.0002196562,0.0005608074],"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":[0.0001075274,0.000129007,0.002740618,0.0003820313,0.00007395626,0.0005721051,0.00121336,0.0003619134,0.0003325305,0.5991881,0.1208887,0.2740102],"study_design_scores_gemma":[0.00003176719,0.00006361445,0.003437422,0.000881362,0.00002107795,0.001089821,0.000523376,0.00007853044,0.0001345425,0.1135658,0.8801556,0.00001713869],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.009139215,0.3667458,0.002442646,0.3277884,0.009847232,0.00002333041,0.000210015,0.00009817581,0.2837053],"genre_scores_gemma":[0.4096804,0.2409395,0.006830367,0.2007255,0.01890232,0.0001415504,0.0004207114,0.0001373905,0.1222222],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01252312,"threshold_uncertainty_score":0.04189402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01131596444065745,"score_gpt":0.2617101666602155,"score_spread":0.250394202219558,"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."}}