{"id":"W4285225080","doi":"10.2139/ssrn.4087991","title":"Whole Genome Alignment: Algorithmic Aspects and Current Challenges","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Current (fluid); Genome; Computational biology; Computer science; Data science; Biology; Genetics; Engineering; Electrical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009265672,0.0001723853,0.0001381623,0.00008634463,0.0003449991,0.00002994612,0.000273709,0.00003911584,0.00003543358],"category_scores_gemma":[0.000009308594,0.0001779553,0.00008300711,0.00007099401,0.00003701207,0.00000551161,0.0002807052,0.0008256063,0.00001069263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003213227,"about_ca_system_score_gemma":0.0005212025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003644203,"about_ca_topic_score_gemma":0.00003301093,"domain_scores_codex":[0.9977261,0.0001190156,0.0001850623,0.0003314276,0.0002835048,0.001354834],"domain_scores_gemma":[0.9995521,0.000004158431,0.000110037,0.0002022849,0.0000335711,0.00009785876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000174632,0.0006565637,0.0005242041,0.00005888742,0.001219517,0.0000343432,0.0008657846,0.000371319,0.466707,0.02863818,0.0004518493,0.5002977],"study_design_scores_gemma":[0.003082829,0.003482198,0.002357041,0.00001010284,0.0001149948,0.002841609,0.005727696,0.0001094772,0.00154934,0.06809928,0.911764,0.0008613822],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5194373,0.4726388,0.003003988,0.002342937,0.0006444108,0.0004595464,0.00004458844,0.00002855518,0.001399896],"genre_scores_gemma":[0.9239843,0.07418457,0.00008586139,0.00005261204,0.0006201721,0.0000408181,0.00006281037,0.00003928991,0.000929569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9113122,"threshold_uncertainty_score":0.7256806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009513101580729192,"score_gpt":0.228827964580948,"score_spread":0.2193148630002188,"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."}}