{"id":"W2559115594","doi":"","title":"Proteome Analyst: An Overview","year":2004,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Gene ontology; Computer science; Upload; Parsing; UniProt; Proteome; Ontology; Classifier (UML); Set (abstract data type); Function (biology); Class (philosophy); Natural language processing; Computational biology; Artificial intelligence; Gene; Bioinformatics; Biology; Programming language; World Wide Web; Genetics","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":[0.0001180172,0.00008665235,0.00007310535,0.00002341648,0.00004238167,0.0000221228,0.000149632,0.00007264574,0.00009946549],"category_scores_gemma":[0.00003856963,0.00007124287,0.00004598184,0.00006752295,0.00002406898,0.000003710551,0.0000580519,0.00006081114,0.00006857976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007630479,"about_ca_system_score_gemma":0.00004026958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003847388,"about_ca_topic_score_gemma":0.00005182617,"domain_scores_codex":[0.9994918,0.00001765062,0.0001346114,0.0001319056,0.00008847403,0.0001355972],"domain_scores_gemma":[0.9995262,9.994673e-7,0.00004215204,0.0003313269,0.00003214773,0.00006716458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001350107,0.0006116152,0.01604433,0.0003695762,0.0003070144,0.00001733462,0.0006291699,0.0210081,0.8901386,0.04602784,0.003486636,0.02122475],"study_design_scores_gemma":[0.003752925,0.003061672,0.02986655,0.00007131224,0.00007809976,0.0002170211,0.0002788397,0.002873427,0.5751605,0.004523871,0.3785689,0.001546905],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9499525,0.0004978038,0.0187831,0.0004541477,0.000076507,0.0002920351,0.000004950374,0.00006603661,0.02987295],"genre_scores_gemma":[0.9648738,0.0001064084,0.03207585,0.001210642,0.0001449848,0.00001343286,0.0001365586,0.00001611977,0.001422195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3750822,"threshold_uncertainty_score":0.29052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02055593078039349,"score_gpt":0.3137011652168754,"score_spread":0.2931452344364819,"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."}}