{"id":"W2024238986","doi":"10.1016/s1741-8372(04)02453-3","title":"Christophe Echeverri: from Canada to Cenix","year":2004,"lang":"en","type":"article","venue":"Drug Discovery Today TARGETS","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"RNA interference; Management; Library science; Political science; Engineering; Biology; Computer science; RNA; Genetics; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032215,0.0008704943,0.0009628347,0.001884796,0.005839556,0.005045716,0.001596148,0.003929208,0.1337163],"category_scores_gemma":[0.007817032,0.0003849659,0.0004623882,0.002225278,0.002278607,0.003070994,0.003489984,0.004872284,0.03021203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03251576,"about_ca_system_score_gemma":0.04764991,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7847192,"about_ca_topic_score_gemma":0.7947161,"domain_scores_codex":[0.9967688,0.0002541488,0.00007214762,0.0004748664,0.001604132,0.0008259031],"domain_scores_gemma":[0.9906242,0.0004364509,0.0001313328,0.0001830051,0.004577274,0.004047767],"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":[0.0001251412,0.00002478995,0.000997751,0.00009481089,0.00001632987,0.0004628681,0.000283103,0.000281011,0.0005010022,0.02471581,0.9106891,0.06180812],"study_design_scores_gemma":[0.00001086378,0.000006813139,0.0004931291,0.00005496711,0.000004363621,0.0002300796,0.0002846275,0.00006783617,0.0002781837,0.001348026,0.9972006,0.00002066759],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.003602391,0.08002196,0.00708121,0.6700036,0.07007539,0.0001421078,0.002613253,0.001358012,0.165102],"genre_scores_gemma":[0.04523288,0.03285813,0.00475888,0.05369527,0.004341574,0.0000629677,0.0009018464,0.0007438938,0.8574045],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2152808,"threshold_uncertainty_score":0.4473257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00687837313704136,"score_gpt":0.2338614721404218,"score_spread":0.2269830990033805,"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."}}