{"id":"W2105389823","doi":"10.1186/gb-2009-10-3-r29","title":"TFCat: the curated catalog of mouse and human transcription factors","year":2009,"lang":"en","type":"article","venue":"Genome biology","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":213,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University and Génome Québec Innovation Centre; Child and Family Research Institute; McGill University; University of British Columbia","funders":"National Institute of Allergy and Infectious Diseases; Ontario Institute for Cancer Research; National Institutes of Health; Michael Smith Health Research BC; Canadian Institutes of Health Research; McGill University Health Centre; McGill University","keywords":"Computational biology; Transcription factor; Biology; Computer science; Information retrieval; Homology (biology); Function (biology); World Wide Web; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007649695,0.0001028836,0.0001171746,0.00002372944,0.00007642377,0.000006479141,0.0001470566,0.0001313339,0.00000783903],"category_scores_gemma":[0.000007302758,0.00007287386,0.00004403255,0.00003678016,0.0001201902,0.000001264461,0.00002652103,0.00005110895,0.000001208142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005827233,"about_ca_system_score_gemma":0.00001533588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003741584,"about_ca_topic_score_gemma":0.00004402979,"domain_scores_codex":[0.9994489,0.00003693637,0.0001628016,0.0001824485,0.00002287175,0.0001460191],"domain_scores_gemma":[0.9996433,0.000003910221,0.0000712902,0.0002179079,0.00003176707,0.00003177477],"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":[0.000009374039,0.00002210262,0.001950092,0.000003776942,0.00001905615,1.207739e-7,0.00009623518,0.00001068161,0.9965476,0.001037254,0.0000219772,0.000281724],"study_design_scores_gemma":[0.001377404,0.002941818,0.3495115,0.000005573198,0.00007544183,0.000032589,0.0005084976,0.00007762232,0.613015,0.003055623,0.02876626,0.0006326368],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986414,0.0006054927,0.0001930486,0.0001103052,0.00003909567,0.0001083558,0.00007606737,0.000005820441,0.0002204365],"genre_scores_gemma":[0.9987259,0.0001584419,0.00006167985,0.0001039913,0.00004227831,0.000002443334,0.0007192941,0.000006896678,0.0001791089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3835326,"threshold_uncertainty_score":0.297171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009509502236702279,"score_gpt":0.2310902654413785,"score_spread":0.2215807632046762,"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."}}