{"id":"W2101347991","doi":"10.1093/bioinformatics/btm585","title":"Choosing BLAST options for better detection of orthologs as reciprocal best hits","year":2007,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":535,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reciprocal; Genome; Matching (statistics); Computational biology; Computer science; Gene; Biology; Genetics; Mathematics; Statistics","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":[0.01540145,0.002624437,0.003067904,0.005493366,0.001639209,0.002498676,0.002241461,0.003002172,0.00783434],"category_scores_gemma":[0.04746468,0.001056648,0.001522264,0.004567757,0.0007438138,0.003936914,0.002075787,0.00221811,0.003971528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004344598,"about_ca_system_score_gemma":0.0006930121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003276186,"about_ca_topic_score_gemma":0.0005697493,"domain_scores_codex":[0.9887902,0.005271143,0.002373447,0.001580758,0.001407695,0.000576851],"domain_scores_gemma":[0.9761342,0.017237,0.001648119,0.001805024,0.002402084,0.0007735798],"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":[0.01265645,0.001041672,0.04439763,0.007303128,0.0007083691,0.003217027,0.001613004,0.006637349,0.774065,0.004615853,0.01380727,0.1299372],"study_design_scores_gemma":[0.001279686,0.003419456,0.06599035,0.0016391,0.001214136,0.008095636,0.002434434,0.1257163,0.7232352,0.01609052,0.04997454,0.0009107382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6028555,0.004100505,0.3475278,0.001508781,0.0004203428,0.00103962,0.009453053,0.02808009,0.005014205],"genre_scores_gemma":[0.3463446,0.0006443936,0.6373175,0.0005892671,0.00006128717,0.0009814526,0.009995043,0.003437569,0.0006289431],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01540145,"threshold_uncertainty_score":0.08145154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01455614558782914,"score_gpt":0.2589700547250416,"score_spread":0.2444139091372124,"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."}}