{"id":"W2490276334","doi":"10.4018/978-1-4666-3604-0.ch045","title":"Incorporating Correlations among Gene Ontology Terms into Predicting Protein Functions","year":2013,"lang":"en","type":"book-chapter","venue":"Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Gene ontology; Computational biology; Computer science; Function (biology); Artificial intelligence; Biology; Gene; Evolutionary biology; Genetics; Gene expression","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002413895,0.0005354744,0.0004286199,0.0001600286,0.0003898715,0.0001293331,0.0003732983,0.001166378,0.000167857],"category_scores_gemma":[0.00005789287,0.000515337,0.000232854,0.00004679143,0.0002949002,0.0000337224,0.0003899194,0.000581476,0.000511019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007519936,"about_ca_system_score_gemma":0.000206205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003240432,"about_ca_topic_score_gemma":0.0001558971,"domain_scores_codex":[0.9978229,0.00001514905,0.001211975,0.0002980667,0.0002456855,0.0004062279],"domain_scores_gemma":[0.9976745,0.00002004767,0.001115114,0.0007786041,0.0002022428,0.0002094416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003968933,0.0004537941,0.008649625,0.005406223,0.005909257,0.00005514745,0.007531006,0.009911999,0.02519708,0.1954187,0.3420354,0.3990348],"study_design_scores_gemma":[0.003573153,0.002450814,0.0007468734,0.001512897,0.0009595144,0.0003854737,0.001060072,0.2485736,0.002558342,0.04252753,0.6894205,0.006231275],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.009289885,0.0005441887,0.0902154,0.0001350644,0.001234028,0.002431568,0.0002481677,0.0001548408,0.8957469],"genre_scores_gemma":[0.1060556,0.0001603023,0.1130993,0.000735089,0.002735578,0.000356496,0.009547925,0.0003022393,0.7670075],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3928035,"threshold_uncertainty_score":0.9997298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009257427965719768,"score_gpt":0.1987701369157836,"score_spread":0.1895127089500638,"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."}}