{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003154167,0.0000656283,0.00005710791,0.000007804143,0.00004747409,0.000009152999,0.00002997362,0.00003606063,0.00001202467],"category_scores_gemma":[0.00001113193,0.00006272441,0.00002398028,0.00001753287,0.000009925784,2.454873e-7,0.00009856415,0.0000105117,0.000006237106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004000287,"about_ca_system_score_gemma":0.00002650201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002670849,"about_ca_topic_score_gemma":0.00001169534,"domain_scores_codex":[0.9996034,0.00001644239,0.00007301218,0.0001686316,0.00004576053,0.00009274491],"domain_scores_gemma":[0.9997743,0.000002654068,0.00001989234,0.0001039082,0.00006836019,0.00003092748],"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":[0.000004242709,0.00001480151,0.0004837257,0.000009282046,0.00003881446,0.000001816197,0.00004493924,0.00002378453,0.9894303,0.0001663705,0.0001978254,0.009584118],"study_design_scores_gemma":[0.0002081746,0.00009094079,0.04775668,0.000002863007,0.00001668666,0.0000260449,0.000145015,0.00004177012,0.9123854,0.00006689131,0.0391544,0.0001051328],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9611844,0.03782848,0.00003689694,0.0003047327,0.0001559349,0.00005960744,0.00001883462,0.000002340883,0.0004088205],"genre_scores_gemma":[0.9947451,0.003370765,0.0005721088,0.0002864493,0.0001546996,0.00001410448,0.00003888294,0.000006692799,0.0008112255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07704488,"threshold_uncertainty_score":0.2557827,"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."}}