{"id":"W2148088562","doi":"10.1142/s0219720010005002","title":"A GRAPH-BASED ALGORITHM FOR MINING MULTI-LEVEL PATTERNS IN GENOMIC DATA","year":2010,"lang":"en","type":"article","venue":"Journal of Bioinformatics and Computational Biology","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Guelph","funders":"","keywords":"Genome; Comparative genomics; Genomics; Computer science; Graph; Computational biology; Data mining; Gene; Theoretical computer science; Biology; Genetics","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":[0.0004388966,0.0001020974,0.0001632959,0.000160168,0.00003958043,0.00002232607,0.0002589399,0.0001075364,0.000003787225],"category_scores_gemma":[0.0000390115,0.00008781124,0.00005054826,0.00004729227,0.00005730624,0.000011047,0.0001057248,0.0001058216,5.930394e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000532351,"about_ca_system_score_gemma":0.0001153123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000412813,"about_ca_topic_score_gemma":0.00003705373,"domain_scores_codex":[0.9992058,0.00001724728,0.0004520912,0.0001110647,0.0000651232,0.0001486753],"domain_scores_gemma":[0.9993192,0.00005305887,0.000291427,0.000134147,0.0001429578,0.00005919769],"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":[0.0001298747,0.0003175816,0.03271526,0.0001255606,0.0002902465,0.000006102774,0.000300243,0.002820868,0.03362976,0.0001514917,0.0006953267,0.9288177],"study_design_scores_gemma":[0.004224426,0.0007035682,0.03631204,0.00002323468,0.00002993967,0.0001282062,0.0002073146,0.9511013,0.0004609724,0.0005547449,0.006005828,0.0002484438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.406325,0.0001704728,0.5927427,0.0001504334,0.0001850758,0.0001145638,0.0003053297,0.000001374439,0.000004990564],"genre_scores_gemma":[0.24808,0.00007630982,0.7508026,0.0002217924,0.0001350992,0.000003812384,0.0006669362,0.000008203542,0.000005168535],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9482804,"threshold_uncertainty_score":0.3580838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03984766336363813,"score_gpt":0.2978313042449222,"score_spread":0.2579836408812841,"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."}}