{"id":"W2066376202","doi":"10.1145/1923947.1923959","title":"LLS","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; XML; Prefix; Scheme (mathematics); Search engine indexing; Interval (graph theory); Tree (set theory); Set (abstract data type); Information retrieval; Data mining; Programming language; Mathematics; World Wide Web; Combinatorics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001978822,0.0005733102,0.0004783112,0.00201469,0.001003023,0.002857314,0.001556457,0.001157885,0.056993],"category_scores_gemma":[0.00792005,0.0004178422,0.0005499382,0.002058006,0.0006246718,0.005375349,0.002604497,0.001162095,0.04509487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001197481,"about_ca_system_score_gemma":0.00147992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001920539,"about_ca_topic_score_gemma":0.002086468,"domain_scores_codex":[0.9979435,0.0004832593,0.0002586583,0.0003231431,0.0008033668,0.0001880855],"domain_scores_gemma":[0.9939451,0.0008877024,0.0003309985,0.003023438,0.001603876,0.0002089531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004930785,0.0001379897,0.001764429,0.0005480199,0.00003637906,0.0002997208,0.0005751994,0.00260537,0.0171818,0.1435584,0.1985934,0.6342062],"study_design_scores_gemma":[0.00005288924,0.0001372028,0.0007040946,0.0001433812,0.0000244498,0.0004863057,0.0002336513,0.0118309,0.0130103,0.0409834,0.9323448,0.00004863324],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01264933,0.001367248,0.7493247,0.002380099,0.001358278,0.0007920315,0.01218284,0.05898206,0.1609634],"genre_scores_gemma":[0.1845213,0.001784303,0.595152,0.002663028,0.0007154977,0.0008730293,0.03851198,0.006125716,0.169653],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.943007,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004613509425564375,"score_gpt":0.2227759121071394,"score_spread":0.218162402681575,"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."}}