{"id":"W191311471","doi":"","title":"An Algorithm for the Estimation of a Time Period of 2-Sequences.","year":2009,"lang":"en","type":"article","venue":"Indian International Conference on Artificial Intelligence","topic":"Fractal and DNA sequence analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Saint Mary's University; University of New Brunswick","funders":"","keywords":"Period (music); Algorithm; Estimation; Computer science; 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":[0.0001868371,0.00009719883,0.0001157937,0.00007685933,0.0000562407,0.00003550735,0.0004397664,0.00007115797,0.000173262],"category_scores_gemma":[0.0001144297,0.00007581498,0.00009892415,0.00009636306,0.0001707991,0.00001611107,0.00001355696,0.00004833005,0.000013392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001161012,"about_ca_system_score_gemma":0.00009405127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006038061,"about_ca_topic_score_gemma":0.00003225876,"domain_scores_codex":[0.9991471,0.00002358744,0.0003160655,0.0002065914,0.0001974307,0.0001092465],"domain_scores_gemma":[0.9992064,0.00002708629,0.0001836697,0.0002174667,0.0003270745,0.00003834038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009588205,0.0001419754,0.00001490155,0.000002867985,0.00004499765,0.000001264652,0.0002362928,0.004084613,0.3014544,0.01815302,0.00002610311,0.6757437],"study_design_scores_gemma":[0.00003036701,0.0008228586,0.0001137301,0.00002657545,0.00001571268,0.000004265155,0.0003943174,0.3171895,0.6598406,0.02136158,0.00008959127,0.0001108766],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3556417,0.00008227243,0.6384387,0.002746492,0.0002880463,0.0004569408,0.0002594374,0.00001527774,0.002071122],"genre_scores_gemma":[0.99594,0.00004884001,0.003522511,0.0001499087,0.0001012349,0.00001414743,0.0001162268,0.000004473588,0.0001027024],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6756328,"threshold_uncertainty_score":0.3091645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03554230519960595,"score_gpt":0.332159717735415,"score_spread":0.2966174125358091,"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."}}