{"id":"W1964318726","doi":"10.1504/ijfipm.2009.030837","title":"Transcription Factor mapping between Bacteria Genomes","year":2009,"lang":"en","type":"article","venue":"International Journal of Functional Informatics and Personalised Medicine","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Canada","keywords":"Organism; Model organism; Identification (biology); Computational biology; Genome; Biology; Bacterial genome size; Transcription factor; Gene; Genetics; Computer science; Data mining; Ecology","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":[0.0003420115,0.0003863521,0.0005713546,0.001213672,0.000590033,0.0005565075,0.0004573586,0.0004264553,0.00341829],"category_scores_gemma":[0.001860295,0.0002294555,0.0006046171,0.001535106,0.0001642545,0.0005012923,0.000604256,0.0005766755,0.001192802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005015475,"about_ca_system_score_gemma":0.0005788244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002160265,"about_ca_topic_score_gemma":0.001497967,"domain_scores_codex":[0.9995858,0.00007212775,0.00002710006,0.0001479718,0.0001082066,0.00005890973],"domain_scores_gemma":[0.9996687,0.0001421654,0.00004271378,0.00004232419,0.00006758634,0.00003653389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001502009,0.0001202462,0.01204725,0.001231307,0.00008185521,0.0006412152,0.000463737,0.002176864,0.8605255,0.002140618,0.000655904,0.1184134],"study_design_scores_gemma":[0.0001468662,0.001053273,0.125002,0.0004299427,0.0002923221,0.00396823,0.001985818,0.01736752,0.7763671,0.01027717,0.06300038,0.000109342],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.897439,0.007041815,0.08031276,0.0003891347,0.0001533187,0.0002041238,0.00494541,0.0008211681,0.008693329],"genre_scores_gemma":[0.8464623,0.0030979,0.1350412,0.0001103801,0.0000179111,0.0001646272,0.01163083,0.0001502127,0.003324589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00341829,"threshold_uncertainty_score":0.01143533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03203035830305073,"score_gpt":0.2634521672911601,"score_spread":0.2314218089881094,"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."}}