{"id":"W4391054883","doi":"10.14778/3632093.3632118","title":"MOSER: Scalable Network Motif Discovery Using Serial Test","year":2023,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Motif (music); Computer science; Scalability; Graph; Theoretical computer science; Cluster analysis; Network motif; Data mining; Artificial intelligence; Complex network; 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":[0.002652733,0.001465817,0.001946246,0.00294775,0.0008204588,0.001477382,0.003900751,0.001631281,0.00584463],"category_scores_gemma":[0.0192076,0.0006960632,0.001560083,0.002129947,0.0009578331,0.002949586,0.002527155,0.001834524,0.001841133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008732986,"about_ca_system_score_gemma":0.00189438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002970055,"about_ca_topic_score_gemma":0.006753298,"domain_scores_codex":[0.9975708,0.0008193199,0.0001327213,0.0006328662,0.0006542281,0.0001901029],"domain_scores_gemma":[0.989096,0.007082278,0.0008135099,0.001829465,0.0007678951,0.0004109039],"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":[0.002000096,0.000733017,0.02066021,0.0007710044,0.000623719,0.001326883,0.0002770279,0.2485923,0.02198611,0.04619119,0.04397929,0.6128592],"study_design_scores_gemma":[0.00009545242,0.00008624394,0.0005250935,0.000008270157,0.00002049724,0.0001629468,0.00002554221,0.9725008,0.003010887,0.02177145,0.001776125,0.0000166964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04208329,0.0004338933,0.9314539,0.0005797541,0.0001444296,0.0002932952,0.00197897,0.02095603,0.002076448],"genre_scores_gemma":[0.3805958,0.0002154299,0.6070479,0.0005195547,0.0001691215,0.0006604471,0.006426346,0.001053737,0.003311645],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00584463,"threshold_uncertainty_score":0.01955223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01541677760382744,"score_gpt":0.2472493557674615,"score_spread":0.2318325781636341,"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."}}