{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005935714,0.0001793373,0.0002119986,0.001213572,0.001111479,0.000304899,0.0004996688,0.0002068142,0.000005709194],"category_scores_gemma":[0.00007613208,0.0002246061,0.00005877139,0.001204484,0.0001041893,0.007333199,0.0001891493,0.000159556,0.000006882133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000355304,"about_ca_system_score_gemma":0.0002341329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001506403,"about_ca_topic_score_gemma":0.000008392743,"domain_scores_codex":[0.9980075,0.0003305529,0.0003786114,0.0003784924,0.00060097,0.0003039131],"domain_scores_gemma":[0.9977438,0.0001275494,0.0002765839,0.0002852777,0.001407484,0.0001592557],"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":[0.001576533,0.001042473,0.005543335,0.0007718759,0.0002400067,0.00006606932,0.01797084,0.0369582,0.2666793,0.6192978,0.005020149,0.04483345],"study_design_scores_gemma":[0.004091864,0.003062129,0.01032095,0.0001856812,0.00008181135,0.00007023115,0.003255778,0.8346907,0.04242476,0.001967817,0.09884221,0.001006077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1046189,0.00002718984,0.8907748,0.0002063945,0.00009507372,0.001254635,0.00002738064,0.0001400444,0.002855587],"genre_scores_gemma":[0.9948693,0.0001454554,0.003310329,0.0000454763,0.00003666901,0.000002277219,0.001016319,0.000007505927,0.0005666898],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8902504,"threshold_uncertainty_score":0.9159172,"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."}}