{"id":"W2325692381","doi":"10.2174/1875692111008010004","title":"Editorial [Personalized Vaccines and Public Health Genomics: Anticipating and Monitoring the ELSIs]","year":2010,"lang":"en","type":"article","venue":"Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine","topic":"Science, Research, and Medicine","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Genomics; Personalized medicine; Public health; Medicine; Virology; Computational biology; Internet privacy; Bioinformatics; Computer science; Biology; Genetics; Genome; Nursing; Gene","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":[0.007279537,0.004991175,0.005519551,0.00460349,0.0036978,0.007321812,0.005685249,0.02961885,0.009788473],"category_scores_gemma":[0.0273284,0.001626596,0.004723054,0.002164903,0.003530437,0.003964958,0.001304931,0.02703799,0.009940214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003072837,"about_ca_system_score_gemma":0.002423279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003518388,"about_ca_topic_score_gemma":0.006285942,"domain_scores_codex":[0.9944906,0.001058552,0.0008222719,0.0009263206,0.002221555,0.0004806302],"domain_scores_gemma":[0.9744753,0.01201522,0.001481082,0.0007482267,0.008975886,0.002304294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006718326,0.00002565397,0.00004342743,0.0002882925,0.00006162901,0.0001425849,0.000008936616,0.00004583436,0.00007449385,0.0003466938,0.9938015,0.005093773],"study_design_scores_gemma":[0.0001544158,0.00007889444,0.0007767011,0.0006396595,0.0002764844,0.0004615517,0.00003443105,0.000459941,0.0002692048,0.00171931,0.9950687,0.0000607216],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0000483349,0.003954144,0.0002046702,0.0335468,0.9609373,0.00003213942,0.0000797379,0.00007048801,0.001126361],"genre_scores_gemma":[0.0005411898,0.002730913,0.0001737615,0.0433033,0.9493139,0.00002743185,0.00003273028,0.00002253764,0.003854053],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.02961885,"threshold_uncertainty_score":0.03849828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1394158404100169,"score_gpt":0.4378566691323411,"score_spread":0.2984408287223242,"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."}}