{"id":"W4255149369","doi":"10.22215/etd/2017-12009","title":"Navigating Molecular Evolution Using Substitution Mappings","year":2017,"lang":"en","type":"dissertation","venue":"","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Substitution (logic); Amino acid substitution; Computer science; Substitution method; Amino acid; Bayesian probability; Type (biology); Molecular evolution; Algorithm; Artificial intelligence; Chemistry; Phylogenetic tree; Biology; Mutation; Biochemistry; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001985349,0.0006172036,0.0006627786,0.00138692,0.000679712,0.001123955,0.001008324,0.001131572,0.004231129],"category_scores_gemma":[0.008952496,0.0005768536,0.001109656,0.0009355431,0.0006502691,0.001863596,0.001505274,0.0009798603,0.0007217265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005717594,"about_ca_system_score_gemma":0.0008268385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001817112,"about_ca_topic_score_gemma":0.002186596,"domain_scores_codex":[0.9994441,0.0003115749,0.00003262212,0.0001120278,0.00007374302,0.00002597239],"domain_scores_gemma":[0.9966127,0.002717763,0.0001221525,0.0003170673,0.0001569897,0.00007339133],"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":[0.0001999942,0.0001433643,0.01398312,0.0002395549,0.0001566306,0.0003196737,0.0009430994,0.7873105,0.008621654,0.07279438,0.002189953,0.1130981],"study_design_scores_gemma":[0.00002337525,0.00003714644,0.0003853535,0.00001528436,0.00000933414,0.00005730814,0.00005692359,0.9601722,0.001162367,0.03623428,0.001835506,0.00001096297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1467235,0.0001707793,0.8434829,0.000350925,0.00005577643,0.0001271324,0.0007017757,0.004390775,0.003996569],"genre_scores_gemma":[0.4401425,0.0002433166,0.5563843,0.0001069473,0.00001986611,0.0003994205,0.001047945,0.0005046193,0.001151146],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004231129,"threshold_uncertainty_score":0.01415455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0144844631590265,"score_gpt":0.2941442816988417,"score_spread":0.2796598185398152,"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."}}