{"id":"W2156644391","doi":"10.1080/10635150390196993","title":"Accelerated Likelihood Surface Exploration: The Likelihood Ratchet","year":2003,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Directorate for Biological Sciences; Simon Fraser University","keywords":"Tree (set theory); Algorithm; Set (abstract data type); Heuristic; Inference; Tree rearrangement; Mathematical optimization; Mathematics; Computer science; Local optimum; Phylogenetic tree; Artificial intelligence; Biology; Combinatorics","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":[0.00477117,0.0008785713,0.001584603,0.001771646,0.0009334628,0.001655467,0.002596276,0.001936487,0.004767026],"category_scores_gemma":[0.02538486,0.0009786492,0.001366078,0.001280894,0.00222313,0.002922907,0.004115281,0.002281846,0.001280399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001041923,"about_ca_system_score_gemma":0.001782385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002147336,"about_ca_topic_score_gemma":0.002141754,"domain_scores_codex":[0.9984514,0.0007345129,0.00006489194,0.0001990655,0.0004401088,0.0001099995],"domain_scores_gemma":[0.9896495,0.007714108,0.0004117126,0.00104225,0.0009177124,0.0002646008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004110798,0.0001328265,0.003935351,0.0003068475,0.0001674305,0.0003176678,0.0005831862,0.4200823,0.008987787,0.2087718,0.005808929,0.3504948],"study_design_scores_gemma":[0.00004432267,0.00007508357,0.0002331002,0.00002346977,0.00001861262,0.00009235004,0.00002502768,0.946793,0.001138458,0.04850186,0.003032479,0.00002224089],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007514902,0.0002731735,0.9899732,0.0002202474,0.00005447654,0.00004913947,0.00002260962,0.0006689635,0.001223207],"genre_scores_gemma":[0.1644994,0.0004499972,0.8297364,0.0002601842,0.0001388136,0.0004616718,0.0001407574,0.0006382536,0.003674665],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00477117,"threshold_uncertainty_score":0.02523267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02734373941693108,"score_gpt":0.2585332501050232,"score_spread":0.2311895106880921,"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."}}