{"id":"W2118769225","doi":"10.1093/nar/gki027","title":"PSORTdb: a protein subcellular localization database for bacteria","year":2004,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":135,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Genome British Columbia; Genome Canada; Genome Prairie; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Michael Smith Health Research BC; National Science Foundation","keywords":"Biology; Identification (biology); Annotation; Database; Bacterial genome size; Computational biology; Function (biology); Protein function; Genome; Database search engine; Computer science; Information retrieval; Bioinformatics; Search engine; Data mining; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005077466,0.001497607,0.001688759,0.003077742,0.0008431411,0.001516727,0.00175839,0.001157887,0.01243724],"category_scores_gemma":[0.001449951,0.0006319709,0.0009490086,0.003740744,0.0002506583,0.001631725,0.001611404,0.001460343,0.02359797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006700861,"about_ca_system_score_gemma":0.001774822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002241847,"about_ca_topic_score_gemma":0.002355011,"domain_scores_codex":[0.9996761,0.00003869894,0.00006495926,0.00008406923,0.00009108883,0.00004510561],"domain_scores_gemma":[0.9995624,0.00005583759,0.00008703616,0.0000880732,0.0001054127,0.0001011645],"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":[0.002038852,0.0002410943,0.003976204,0.005493015,0.0002304172,0.0008450525,0.0002954113,0.00306969,0.0713085,0.009051722,0.7988518,0.1045982],"study_design_scores_gemma":[0.0004302207,0.0001872802,0.007155327,0.000329354,0.0001509747,0.001433004,0.0001304719,0.006457821,0.01478557,0.009679311,0.9591544,0.0001063724],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.01624337,0.007596121,0.05816744,0.000890872,0.0003367653,0.0003163157,0.8516898,0.05111445,0.01364488],"genre_scores_gemma":[0.01141179,0.002305439,0.03191081,0.0002068096,0.00003969476,0.0002343601,0.9503447,0.001267802,0.002278541],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01243724,"threshold_uncertainty_score":0.04160666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03065818731062588,"score_gpt":0.3387933180577546,"score_spread":0.3081351307471287,"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."}}