{"id":"W2103184043","doi":"10.1093/bioinformatics/bti321","title":"MtbRegList, a database dedicated to the analysis of transcriptional regulation in Mycobacterium tuberculosis","year":2005,"lang":"en","type":"article","venue":"Computer applications in the biosciences","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; U.S. National Library of Medicine; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Mycobacterium tuberculosis; Tuberculosis; Database; Computational biology; Biology; Computer science; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007618313,0.001572927,0.002028554,0.004630342,0.0009530249,0.002071919,0.001986639,0.001581793,0.0277407],"category_scores_gemma":[0.003934321,0.0006935192,0.0007682014,0.005564366,0.0004247234,0.001354162,0.001277182,0.001053568,0.02191645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006768923,"about_ca_system_score_gemma":0.001941754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002480211,"about_ca_topic_score_gemma":0.003450504,"domain_scores_codex":[0.9991804,0.0001170122,0.000142664,0.0002266106,0.0002349378,0.00009836687],"domain_scores_gemma":[0.9983523,0.0006016979,0.0003436686,0.000241541,0.0001981654,0.0002626482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.007110401,0.000409975,0.01814873,0.01675937,0.0003194978,0.002266587,0.0008246565,0.00431577,0.1868972,0.00500456,0.4714833,0.28646],"study_design_scores_gemma":[0.0005062668,0.0003783633,0.02779083,0.0008919585,0.0003983189,0.002123337,0.0002097368,0.00567876,0.04227784,0.003456613,0.9161503,0.0001378383],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03591984,0.01764063,0.02942493,0.0010595,0.0003309455,0.000377345,0.8199856,0.07776483,0.01749636],"genre_scores_gemma":[0.03931412,0.003770106,0.03442223,0.0004157358,0.0001209951,0.0003753988,0.914216,0.002887242,0.004478338],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0277407,"threshold_uncertainty_score":0.09280187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03446879600612759,"score_gpt":0.3397371658698042,"score_spread":0.3052683698636766,"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."}}