{"id":"W2098676247","doi":"10.1093/nar/gkq1093","title":"PSORTdb--an expanded, auto-updated, user-friendly protein subcellular localization database for Bacteria and Archaea","year":2010,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Biology; Archaea; Bacteria; Database; Bacterial protein; Computational biology; Genetics; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00177879,0.0001915433,0.0001593158,0.0001357242,0.0003409191,0.0001379827,0.0004281666,0.0002906738,0.0001428619],"category_scores_gemma":[0.0007522943,0.0001793298,0.00004418478,0.0001664231,0.000337737,0.00004123881,0.0004278876,0.0005317191,0.0000251342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001578419,"about_ca_system_score_gemma":0.0001226186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005554453,"about_ca_topic_score_gemma":0.00007740568,"domain_scores_codex":[0.998072,0.0001954319,0.0002907136,0.0004160854,0.0004025711,0.0006231734],"domain_scores_gemma":[0.9984859,0.00002797462,0.00007496774,0.0008195475,0.0002991155,0.0002924826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002261396,0.00009896448,0.005889031,0.0001495248,0.00002436548,0.000002047308,0.0002301292,0.000007300635,0.9845562,0.001480752,0.004313336,0.003022189],"study_design_scores_gemma":[0.001509886,0.001283434,0.001644852,0.00003344375,0.00001397283,0.0000472521,0.0003345951,0.03282361,0.3313389,0.000175792,0.630338,0.0004563466],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9565959,0.00004804358,0.04159151,0.0001543048,0.0001108293,0.0009609224,0.00009526952,0.00003903544,0.0004041732],"genre_scores_gemma":[0.9553645,0.00003974291,0.04005128,0.00008523346,0.0003822283,0.0001569864,0.002473755,0.00006991807,0.00137636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6532173,"threshold_uncertainty_score":0.7312858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01996824358640841,"score_gpt":0.3300858543855556,"score_spread":0.3101176107991472,"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."}}