{"id":"W2513395528","doi":"10.1145/2905368","title":"Data Structures for Path Queries","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Multiset; Path (computing); Combinatorics; Mathematics; Selection (genetic algorithm); Discrete mathematics; Computer science","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":[0.0001801395,0.0001851158,0.0001646891,0.00009585486,0.0003349675,0.0001311204,0.002899508,0.00008228196,0.00007211844],"category_scores_gemma":[0.00006673886,0.0001158357,0.00006674135,0.0001775908,0.00006542671,0.001321667,0.0001122459,0.00009642701,0.00003922926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003077952,"about_ca_system_score_gemma":0.00006946218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002525167,"about_ca_topic_score_gemma":0.0000106044,"domain_scores_codex":[0.9984723,0.00003248417,0.0002257504,0.0006740252,0.0002863865,0.0003090819],"domain_scores_gemma":[0.9963208,0.0003463802,0.00006485412,0.003072193,0.00007980378,0.0001159423],"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":[0.00001247413,0.00005308561,0.000002551108,0.000005711823,0.00002270904,0.000003121909,0.0000448606,0.00001506588,0.0004114873,0.003850986,0.002696536,0.9928814],"study_design_scores_gemma":[0.003589648,0.0008749908,0.002234583,0.0001950464,0.00006870259,0.0001015696,0.00009995509,0.08355507,0.02080311,0.1416427,0.7455099,0.001324754],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000122372,0.00008262907,0.994123,0.002611825,0.001030228,0.0002288209,0.001487948,0.0002569465,0.00005617252],"genre_scores_gemma":[0.02213085,0.0001197531,0.9765872,0.000317266,0.0001824748,0.00006634235,0.0000456761,0.00002209972,0.0005282885],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9915566,"threshold_uncertainty_score":0.5388055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05610397486646216,"score_gpt":0.3039814926181849,"score_spread":0.2478775177517227,"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."}}