{"id":"W2067201268","doi":"10.1142/s0219720004000788","title":"IDENTIFYING UNIFORMLY MUTATED SEGMENTS WITHIN REPEATS","year":2004,"lang":"en","type":"article","venue":"Journal of Bioinformatics and Computational Biology","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pacific Institute for the Mathematical Sciences; Simon Fraser University","funders":"","keywords":"Mathematics; String (physics); Coin flipping; Combinatorics; Set (abstract data type); Mutation; Prior probability; Algorithm; Mutation rate; Shuffling; Discrete mathematics; Statistics; Computer science; Genetics; Biology; Bayesian probability","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":[0.0003496889,0.00009417631,0.0001709971,0.0001765238,0.0001229881,0.0001223968,0.000330481,0.00005419235,0.000002360529],"category_scores_gemma":[0.00002624333,0.00006804676,0.00004520488,0.0001597439,0.00004981961,0.0007840561,0.0001841136,0.0001370261,0.000007317592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003210561,"about_ca_system_score_gemma":0.000136511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005545502,"about_ca_topic_score_gemma":4.942888e-7,"domain_scores_codex":[0.9989594,0.00002083784,0.000621143,0.0000813616,0.0001887661,0.0001285067],"domain_scores_gemma":[0.9989744,0.00005512399,0.0005628501,0.0001021422,0.0002110014,0.00009452293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001173875,0.0003911192,0.001790971,0.0001742941,0.0004349457,0.0001715193,0.01094206,0.1677173,0.001389088,0.5379751,0.0008156006,0.2780806],"study_design_scores_gemma":[0.002771691,0.0008101757,0.005106668,0.0001926257,0.00001924994,0.002003687,0.0003521054,0.5903797,0.0006815926,0.396758,0.0006301318,0.0002944056],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07470743,0.0001317648,0.9242855,0.0003146,0.0003672526,0.00004348563,0.000006226774,0.00001467749,0.000129107],"genre_scores_gemma":[0.4227263,0.0000415401,0.5768368,0.000330517,0.00003944931,4.212081e-7,0.00001708773,0.000002545713,0.000005269431],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4226623,"threshold_uncertainty_score":0.2774866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01715622109661268,"score_gpt":0.2722669738252626,"score_spread":0.2551107527286499,"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."}}