{"id":"W2109363750","doi":"10.1093/bioinformatics/btq315","title":"Count: evolutionary analysis of phylogenetic profiles with parsimony and likelihood","year":2010,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":491,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Phylogenetic tree; Java; Phylogenetics; Computer science; Source code; Lineage (genetic); Maximum parsimony; Software; Biology; Gene; Programming language; Genetics; Clade","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":[0.004291379,0.002253696,0.003014641,0.007259753,0.002110565,0.003759101,0.003562113,0.001146361,0.04902266],"category_scores_gemma":[0.02041302,0.00164739,0.002952776,0.006574394,0.001005181,0.004896378,0.003100848,0.003661533,0.01422509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009560562,"about_ca_system_score_gemma":0.001906264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001806646,"about_ca_topic_score_gemma":0.002294129,"domain_scores_codex":[0.9977634,0.0008522971,0.0002518818,0.0004705211,0.0005283203,0.0001335311],"domain_scores_gemma":[0.9933009,0.004564815,0.0005903922,0.0006455933,0.0006509102,0.0002473614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001807882,0.0003394526,0.01719544,0.006283438,0.002279739,0.001409923,0.002336941,0.06049934,0.01404984,0.08490808,0.3259012,0.4829887],"study_design_scores_gemma":[0.0005973096,0.0003139613,0.01155834,0.0006310372,0.0008346972,0.00200472,0.0004924831,0.6019543,0.01141767,0.1673874,0.2023945,0.0004135287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01554796,0.0007162609,0.8950194,0.0004561423,0.0002187499,0.0003686341,0.03265414,0.04993447,0.005084446],"genre_scores_gemma":[0.064205,0.0005164222,0.8689741,0.0001510783,0.000134391,0.001471386,0.03668071,0.02464291,0.003223941],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04902266,"threshold_uncertainty_score":0.1639971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005104281382279222,"score_gpt":0.203892047635604,"score_spread":0.1987877662533248,"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."}}