{"id":"W2136104033","doi":"10.1093/bioinformatics/btm225","title":"Homology search for genes","year":2007,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"U.S. Public Health Service","keywords":"Gene; Homology (biology); Gene prediction; Genome; Annotation; Gene Annotation; Exon; Genetics; Computational biology; Biology; Computer science; Human genome; Ensembl; Genomics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006687936,0.000138635,0.0001299578,0.00006318209,0.0001180498,0.0000291415,0.0002207822,0.0002150144,0.0000103389],"category_scores_gemma":[0.00002007805,0.0001260336,0.000102124,0.00007273247,0.00008200185,0.000005884644,0.0001059716,0.000070155,0.00003860842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001365009,"about_ca_system_score_gemma":0.00006398826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002889052,"about_ca_topic_score_gemma":0.000015576,"domain_scores_codex":[0.9989429,0.000006227505,0.000403806,0.0001070239,0.00009846995,0.0004415492],"domain_scores_gemma":[0.9993533,0.00002872136,0.00008842805,0.0003101483,0.0001071491,0.0001121751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008245988,0.0002119231,0.004109663,0.0006909702,0.0004243198,0.000005631072,0.001656377,0.001069404,0.06046123,0.02383563,0.07670341,0.8300068],"study_design_scores_gemma":[0.002336608,0.001162002,0.001295226,0.00001825717,0.00004704505,0.0001446168,0.001442399,0.02109403,0.1533345,0.0007518344,0.8175195,0.000854019],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1319124,0.000655515,0.8520949,0.000122155,0.0005113751,0.0005693209,0.00005389066,0.000031063,0.01404929],"genre_scores_gemma":[0.7649097,0.0003697652,0.2275815,0.002345352,0.0013702,0.00003847488,0.0008423317,0.00006138562,0.002481221],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8291528,"threshold_uncertainty_score":0.5139502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01585314769633712,"score_gpt":0.2663310844368851,"score_spread":0.250477936740548,"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."}}