{"id":"W4254694878","doi":"10.32920/14638791.v1","title":"Efficient computation of spaced seeds","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heuristics; Heuristic; Computer science; Software; Computation; Quadratic equation; Algorithm; Speedup; Range (aeronautics); Artificial intelligence; Mathematics; Parallel computing; Engineering; Programming language","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":[0.0001742943,0.0001476656,0.0002608431,0.000101363,0.00003764119,0.0001581024,0.0007118181,0.0001268363,0.00002159423],"category_scores_gemma":[0.00001513741,0.0001264862,0.00009976816,0.0001886184,0.0000226229,0.00005263077,0.00353575,0.000208936,0.000007887286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002776202,"about_ca_system_score_gemma":0.0001680921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001461019,"about_ca_topic_score_gemma":0.00000326944,"domain_scores_codex":[0.9986953,0.00006045285,0.0002720268,0.0004668844,0.0003704156,0.0001349386],"domain_scores_gemma":[0.9987454,0.00004058201,0.0001964845,0.0007475524,0.0002107775,0.00005922264],"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":[0.000006104397,0.000440406,0.0001216954,0.0004091388,0.0000781651,0.0000392631,0.001789243,0.8750149,0.002221821,0.01672724,0.00254722,0.1006048],"study_design_scores_gemma":[0.0001209458,0.00001641818,0.001305336,0.0001703635,0.000005413464,0.000003489791,0.00003802492,0.9953138,0.002274739,0.0005193877,0.00008601986,0.0001460431],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03760092,0.0002483375,0.9588804,0.0001993025,0.000951774,0.0001326778,0.00000595893,0.0001103455,0.001870267],"genre_scores_gemma":[0.6334695,0.000008568251,0.3662929,0.00004541779,0.00003727326,0.000004607027,0.00004793753,0.000005493667,0.00008826849],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5958686,"threshold_uncertainty_score":0.5157958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01908596142322564,"score_gpt":0.2688779504802859,"score_spread":0.2497919890570603,"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."}}