{"id":"W2027941709","doi":"10.1109/ijcbs.2009.124","title":"Mapping Transcription Factors from a Model to a Non-model Organism","year":2009,"lang":"en","type":"article","venue":"","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Organism; Model organism; Transcription factor; Transcription (linguistics); Computational biology; Computer science; Biology; Identification (biology); Gene; Genetics; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003072585,0.0003702322,0.000573437,0.0005055546,0.000558804,0.0005576268,0.0005365686,0.0004916996,0.00146128],"category_scores_gemma":[0.000872533,0.0002621318,0.0006608935,0.0003945942,0.0003426046,0.0006000381,0.0004859813,0.0006875857,0.000613874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003407368,"about_ca_system_score_gemma":0.0004045449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006143613,"about_ca_topic_score_gemma":0.0008073947,"domain_scores_codex":[0.9997723,0.00005036301,0.00001704771,0.00007783768,0.00006453045,0.0000180641],"domain_scores_gemma":[0.999603,0.0001845009,0.00004770987,0.00009417609,0.00003630019,0.00003438193],"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":[0.0003146707,0.000105881,0.003968521,0.000252065,0.00003297788,0.0002983931,0.00009756415,0.001891893,0.9788812,0.001162828,0.00009555808,0.01289829],"study_design_scores_gemma":[0.00004016761,0.001475398,0.01846515,0.0000647646,0.0001601677,0.002007305,0.0005779087,0.02752145,0.9320939,0.005230988,0.01231609,0.00004685632],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8759028,0.0008000045,0.119164,0.0002714772,0.0000827078,0.00009656537,0.0005611588,0.0004072042,0.002714163],"genre_scores_gemma":[0.8196901,0.001321478,0.1741484,0.00008288856,0.000009695457,0.0001218129,0.002449347,0.0001090962,0.00206712],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00146128,"threshold_uncertainty_score":0.004888415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02042481401263041,"score_gpt":0.2303280994215822,"score_spread":0.2099032854089518,"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."}}