{"id":"W2998529453","doi":"10.1109/csci46756.2018.00240","title":"On Evaluation of Graph Pattern Matching in Large Databases","year":2018,"lang":"en","type":"article","venue":"","topic":"Graph Theory and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Computer science; Reachability; Graph database; Factor-critical graph; Graph; Matching (statistics); Theoretical computer science; Graph factorization; Pattern matching; Data mining; Line graph; Artificial intelligence; Mathematics; Voltage graph","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":[0.01957219,0.002590796,0.004006983,0.01094246,0.001802821,0.003671443,0.005080529,0.003739504,0.005023197],"category_scores_gemma":[0.07458735,0.000601644,0.00142894,0.01430527,0.001178816,0.009629718,0.00281247,0.001238879,0.001135856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004023884,"about_ca_system_score_gemma":0.002819733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01577646,"about_ca_topic_score_gemma":0.01108865,"domain_scores_codex":[0.9688236,0.01115008,0.003967856,0.004956451,0.009671747,0.001430341],"domain_scores_gemma":[0.9303657,0.05212694,0.00271519,0.006901939,0.005975848,0.001914427],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.009024603,0.003987796,0.03277577,0.003152034,0.001403417,0.0009040469,0.0004097932,0.2489422,0.007949774,0.01262754,0.0470816,0.6317415],"study_design_scores_gemma":[0.0005342826,0.001098998,0.006736073,0.00008535911,0.0002259451,0.0005722098,0.0004904343,0.9719087,0.005390056,0.008479563,0.004433517,0.00004483364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.775411,0.03001356,0.1416622,0.003673272,0.001741746,0.001534231,0.009987494,0.01375704,0.02221954],"genre_scores_gemma":[0.8132731,0.002534215,0.1669512,0.0005273354,0.000262046,0.000311208,0.01340604,0.0003808513,0.002353929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01957219,"threshold_uncertainty_score":0.1035088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04013647443571729,"score_gpt":0.314112528511913,"score_spread":0.2739760540761957,"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."}}