{"id":"W2400935260","doi":"10.1137/1.9781611973440.88","title":"Efficient Matching of Substrings in Uncertain Sequences","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Substring; Subsequence; Computer science; Sequence (biology); Matching (statistics); Scalability; Trajectory; Data mining; Theoretical computer science; Data structure; Mathematics; Programming language; Database","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002045888,0.0005502617,0.001540761,0.00249132,0.0008524773,0.001651093,0.002188769,0.001798693,0.00181453],"category_scores_gemma":[0.01723412,0.0007287994,0.001190476,0.003625065,0.001021594,0.004431755,0.00194102,0.00168579,0.0007108235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008516095,"about_ca_system_score_gemma":0.001181712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001912434,"about_ca_topic_score_gemma":0.001640888,"domain_scores_codex":[0.9973415,0.0003904324,0.0003093985,0.000923053,0.0008614177,0.0001742879],"domain_scores_gemma":[0.9907666,0.006266254,0.001192934,0.0007930853,0.0007381552,0.000242922],"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":[0.0005506719,0.0001701481,0.01106279,0.0004795519,0.0001537484,0.0007401035,0.0005798985,0.5759268,0.01353281,0.05457681,0.002598932,0.3396276],"study_design_scores_gemma":[0.00000942043,0.00006146337,0.0007558838,0.00002613826,0.00001761666,0.00021594,0.0001018087,0.9300213,0.004866533,0.06223563,0.001671153,0.00001708776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.032784,0.0002022746,0.9657217,0.000194531,0.00002297161,0.00005351771,0.0002629031,0.0003276104,0.0004305663],"genre_scores_gemma":[0.3679143,0.0004707317,0.6278046,0.0001962887,0.0001011135,0.00017331,0.001656633,0.0002279011,0.001455069],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00249132,"threshold_uncertainty_score":0.01081979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01540583498905401,"score_gpt":0.2560108658142202,"score_spread":0.2406050308251662,"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."}}