{"id":"W3213420921","doi":"10.3390/genes12111809","title":"Post-Alignment Adjustment and Its Automation","year":2021,"lang":"en","type":"article","venue":"Genes","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multiple sequence alignment; Pairwise comparison; Alignment-free sequence analysis; Sequence (biology); Computational biology; Computer science; Sequence alignment; Automation; Position (finance); Phylogenetic tree; Genetics; Biology; Artificial intelligence; Data mining; Peptide sequence; Gene; Engineering","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":[0.005766599,0.002551552,0.001902782,0.003223097,0.001753033,0.002675024,0.00284799,0.0009706139,0.01798582],"category_scores_gemma":[0.02055064,0.001151648,0.002168369,0.004306739,0.0009911758,0.002092426,0.002756766,0.003685854,0.01896886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006885844,"about_ca_system_score_gemma":0.001980652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002043068,"about_ca_topic_score_gemma":0.002077323,"domain_scores_codex":[0.9947214,0.0009976525,0.0006598296,0.00188075,0.001359803,0.0003806355],"domain_scores_gemma":[0.9894018,0.002913429,0.0009280671,0.003135593,0.003421874,0.0001992894],"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":[0.0005338888,0.0001442363,0.003552163,0.001218151,0.0002171573,0.0004971534,0.0012124,0.006141496,0.1094451,0.01111125,0.0224968,0.8434301],"study_design_scores_gemma":[0.0001246043,0.0006157993,0.015096,0.0002773759,0.0004808815,0.001738301,0.0008877249,0.1705604,0.3775276,0.02997071,0.4022492,0.0004714487],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01500175,0.000690926,0.9641274,0.0002056634,0.0005115633,0.0004045628,0.000939645,0.01485267,0.00326586],"genre_scores_gemma":[0.04630078,0.0004679599,0.9411255,0.0001709405,0.0001556912,0.0004790494,0.002929231,0.004002236,0.004368655],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01798582,"threshold_uncertainty_score":0.06016856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009641345948823139,"score_gpt":0.2281241134630096,"score_spread":0.2184827675141865,"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."}}