{"id":"W2107387420","doi":"10.1093/sysbio/syp103","title":"Inferring and Validating Horizontal Gene Transfer Events Using Bipartition Dissimilarity","year":2010,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Heuristic; Tree (set theory); Context (archaeology); Horizontal gene transfer; Identification (biology); Algorithm; Time complexity; Polynomial; Reliability (semiconductor); Computer science; Exponential function; Reticulate; Biology; Mathematics; Artificial intelligence; Phylogenetic tree; Gene; Combinatorics; Genetics; Physics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003168721,0.0001387398,0.0002442962,0.00002944674,0.0001263431,0.00001427637,0.00008822614,0.0001681218,0.000004061152],"category_scores_gemma":[0.00008336266,0.0001159667,0.00005497213,0.00003035723,0.00006892096,9.891465e-7,0.0001109782,0.00009086292,0.000001113372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005167155,"about_ca_system_score_gemma":0.00002136525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003294776,"about_ca_topic_score_gemma":0.00009479476,"domain_scores_codex":[0.9991163,0.0001002507,0.0002851508,0.000263335,0.0000408802,0.0001940779],"domain_scores_gemma":[0.9996123,0.00001828161,0.00005888436,0.0002127623,0.00004164997,0.00005610118],"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":[0.000005760804,0.00001351076,0.05085969,0.0006561342,0.00006217718,3.993556e-7,0.0000838718,0.000007214624,0.9479187,0.0003540119,4.951541e-7,0.00003809853],"study_design_scores_gemma":[0.001627466,0.0006556032,0.09654882,0.0006155137,0.0003350531,0.0003444296,0.0005296278,0.002064614,0.8918338,0.004342862,0.00008553982,0.001016675],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949312,0.0004268217,0.00387372,0.000023458,0.0003361416,0.0003318816,0.00002162904,0.000004791371,0.00005037886],"genre_scores_gemma":[0.9977632,0.00002112644,0.001966975,0.00003307686,0.0001481541,0.00003207244,0.00001954912,0.00001207803,0.000003779008],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05608483,"threshold_uncertainty_score":0.4728984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02033264634033061,"score_gpt":0.2704887837036182,"score_spread":0.2501561373632876,"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."}}