{"id":"W2114013334","doi":"10.1093/bioinformatics/btr368","title":"SpEED: fast computation of sensitive spaced seeds","year":2011,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Software; Computation; Speedup; Similarity (geometry); Source code; Sequence (biology); Code (set theory); Algorithm; Data mining; Artificial intelligence; Parallel computing; Programming language; Biology; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00007194265,0.00008852278,0.0001073505,0.00003017051,0.00003130195,0.000004088416,0.00006149508,0.00005921088,0.000002940969],"category_scores_gemma":[0.0000156454,0.00008116618,0.00005005251,0.00004689552,0.00006522941,8.908578e-7,0.00007513312,0.00002433874,0.0000111171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003900087,"about_ca_system_score_gemma":0.00002517815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000137526,"about_ca_topic_score_gemma":0.00000652949,"domain_scores_codex":[0.9995433,0.000009368516,0.0002032703,0.00006642209,0.00006597663,0.0001116353],"domain_scores_gemma":[0.9996107,0.000003868205,0.0001210409,0.0001229742,0.0001079628,0.0000334603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003013434,0.000252593,0.02236715,0.000330086,0.0007012715,0.000003810334,0.01990642,0.0006203296,0.9184014,0.001496618,0.003137835,0.03248116],"study_design_scores_gemma":[0.001034151,0.0008913135,0.09169219,0.00003518318,0.00007086632,0.00002842471,0.003431486,0.005942949,0.8936295,0.0004131165,0.002377339,0.0004535125],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9789874,0.0000690856,0.00844183,0.00001113892,0.0001162183,0.0001150302,0.00002822244,0.000003172979,0.01222793],"genre_scores_gemma":[0.9802018,0.00004899727,0.01954729,0.00006577969,0.00003870442,8.546839e-7,0.00002394123,0.000007044381,0.00006561507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06932504,"threshold_uncertainty_score":0.3309861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01992517971629545,"score_gpt":0.22735844778708,"score_spread":0.2074332680707845,"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."}}