{"id":"W2194609845","doi":"10.6000/1927-5129.2015.11.83","title":"Gene Ontology Tools: A Comparative Study","year":2015,"lang":"en","type":"article","venue":"Journal of Basic & Applied Sciences","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Annotation; Ontology; Visualization; Key (lock); Resource (disambiguation); Gene ontology; Information retrieval; Gene Annotation; Data science; World Wide Web; Data mining; Genome; Gene; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001242821,0.00009754005,0.0002498448,0.00006596225,0.00008434863,0.00003973168,0.0004156702,0.00007359728,0.000007400422],"category_scores_gemma":[0.0001479354,0.00006501669,0.00005124504,0.0001645358,0.0005036121,0.000005313755,0.00008071344,0.0001158301,0.000007522647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001317076,"about_ca_system_score_gemma":0.0002945493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004874747,"about_ca_topic_score_gemma":0.00002568228,"domain_scores_codex":[0.9989198,0.00007591872,0.0002989211,0.0001853062,0.0003317225,0.0001882677],"domain_scores_gemma":[0.9993491,0.00004274378,0.0002386428,0.0001145052,0.0001196096,0.0001354156],"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":[0.002423863,0.003588075,0.04401627,0.00002114526,0.0008192306,0.000216715,0.02016781,0.0010001,0.6148621,0.00134489,0.08568694,0.2258528],"study_design_scores_gemma":[0.01625617,0.04747204,0.05644107,0.00006690509,0.0003326817,0.001630218,0.2194133,0.0002396872,0.4244732,0.006359113,0.2256566,0.001659021],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927406,0.0007469649,0.001005998,0.0002713273,0.0002948067,0.00008504642,0.000001368473,0.000004879533,0.004849064],"genre_scores_gemma":[0.9940187,0.00001134126,0.005452753,0.0001870826,0.0002595937,0.000003845161,9.135516e-7,0.00000270807,0.00006310634],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2241938,"threshold_uncertainty_score":0.2651304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1331072111962279,"score_gpt":0.3593847852036112,"score_spread":0.2262775740073833,"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."}}