{"id":"W134625690","doi":"","title":"An Approach to Selecting Putative RNA Motifs Using MDL Principle.","year":2006,"lang":"en","type":"article","venue":"","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Minimum description length; Sequence (biology); Computational biology; RNA; Rank (graph theory); Biology; Computer science; Artificial intelligence; Algorithm; Mathematics; Genetics; Gene; Combinatorics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001911865,0.0004583467,0.0006733602,0.001523721,0.0004162814,0.0006903089,0.001099229,0.0007917828,0.002146101],"category_scores_gemma":[0.0054069,0.0003434309,0.0004875533,0.000610856,0.0004786072,0.0006823595,0.0008016874,0.0006460635,0.0005719196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000832847,"about_ca_system_score_gemma":0.00108618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008427319,"about_ca_topic_score_gemma":0.001049176,"domain_scores_codex":[0.9995333,0.000204875,0.0000323253,0.00005589916,0.0001349014,0.00003878241],"domain_scores_gemma":[0.9975153,0.00152384,0.0002470949,0.0001270851,0.0004671148,0.0001195517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000711965,0.0005116338,0.0111305,0.0004779524,0.0001182212,0.0003558303,0.0001460893,0.5947043,0.05047178,0.03349136,0.003290843,0.3045895],"study_design_scores_gemma":[0.00001789891,0.00004556543,0.0001775342,0.00000574101,0.000004432722,0.00002726868,0.000009522765,0.9940113,0.002663634,0.00269704,0.0003346098,0.000005378274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1085598,0.0002376143,0.8877789,0.0002768971,0.00002913815,0.0002333353,0.0003449321,0.001131859,0.001407584],"genre_scores_gemma":[0.395167,0.00006667658,0.6027578,0.0001052031,0.00001474734,0.0004028061,0.0005914515,0.0001100631,0.000784335],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002146101,"threshold_uncertainty_score":0.01011103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01880239807840648,"score_gpt":0.280094168108652,"score_spread":0.2612917700302455,"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."}}