{"id":"W119709885","doi":"","title":"Genome Homology Visualization by Short Similar Substring Enumeration (Acceleration and Visualization of Computation for Enumeration Problems)","year":2009,"lang":"en","type":"article","venue":"Kyoto University Research Information Repository (Kyoto University)","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics; National Institute of Informatics; Hokkaido University","keywords":"Enumeration; Substring; Visualization; Computation; Genome; Computer science; Data visualization; Homology (biology); Mathematics; Theoretical computer science; Biology; Combinatorics; Algorithm; Genetics; Data structure; Artificial intelligence; Programming language","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008204636,0.0009000439,0.0009273982,0.002121232,0.00058952,0.001622778,0.001655862,0.001431557,0.005133636],"category_scores_gemma":[0.003812695,0.0004748737,0.001067239,0.002603112,0.0006390928,0.003236978,0.002420883,0.001169021,0.001199931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006624783,"about_ca_system_score_gemma":0.0006596445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001996528,"about_ca_topic_score_gemma":0.001345532,"domain_scores_codex":[0.9992871,0.0002416832,0.00003880286,0.0001775549,0.0001767329,0.00007807313],"domain_scores_gemma":[0.9986734,0.0006320336,0.0001501654,0.0003227885,0.0001277682,0.00009392749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007239648,0.0003650427,0.004421269,0.0005288044,0.0001017027,0.0003451704,0.0006244652,0.1189432,0.07318496,0.07154595,0.01773052,0.7114849],"study_design_scores_gemma":[0.00006333834,0.000121023,0.001455987,0.00004199228,0.00001578392,0.0003609748,0.0001056134,0.9083613,0.02305671,0.05678777,0.009587067,0.00004243005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03608199,0.0003909604,0.9520793,0.0003512406,0.00004969191,0.0001028448,0.0004154721,0.00806406,0.002464314],"genre_scores_gemma":[0.1243146,0.0002333985,0.8725792,0.00009284861,0.00003257534,0.0001555364,0.0009312242,0.0002956582,0.001365039],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005133636,"threshold_uncertainty_score":0.01717371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02703116965502951,"score_gpt":0.2791595838563874,"score_spread":0.252128414201358,"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."}}