{"id":"W4297018352","doi":"10.32920/14638791.v2","title":"Efficient computation of spaced seeds","year":2022,"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); Theoretical computer science; Artificial intelligence; Mathematics; Parallel computing; Programming language; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001261099,0.00103858,0.001392465,0.002056562,0.000986635,0.001689629,0.001865061,0.00143055,0.007564401],"category_scores_gemma":[0.01281278,0.0006985146,0.0008011349,0.002145078,0.001101329,0.002569143,0.001809581,0.001149893,0.002267527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001108818,"about_ca_system_score_gemma":0.001404839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001368964,"about_ca_topic_score_gemma":0.001548195,"domain_scores_codex":[0.9986275,0.0002479204,0.00009295226,0.0002656543,0.0006465563,0.0001193692],"domain_scores_gemma":[0.995038,0.002567047,0.0004006165,0.000769622,0.0009517767,0.0002729701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000748077,0.0002187742,0.006272589,0.0006438884,0.0001237732,0.0008607506,0.0005764902,0.4895959,0.04237794,0.1291012,0.01462222,0.3148584],"study_design_scores_gemma":[0.00005539761,0.00009262493,0.0004531713,0.00002969595,0.00001826861,0.0002202228,0.00005076061,0.9054395,0.01377813,0.07523031,0.004605012,0.00002695303],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06591887,0.0003607341,0.9244197,0.0002005087,0.0001155155,0.00008819577,0.0002410261,0.003882332,0.004773175],"genre_scores_gemma":[0.2912382,0.0001772338,0.7044048,0.0000987022,0.00004683682,0.0001356075,0.0006690567,0.001013996,0.002215502],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007564401,"threshold_uncertainty_score":0.02530545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02081935101985498,"score_gpt":0.2787534795356401,"score_spread":0.2579341285157851,"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."}}