{"id":"W3004293141","doi":"10.1017/nws.2020.45","title":"Artificial Benchmark for Community Detection (ABCD)—Fast random graph model with community structure","year":2021,"lang":"en","type":"article","venue":"Network Science","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Community structure; Benchmark (surveying); Random graph; Scalability; Graph; Theoretical computer science; Artificial intelligence; Complex network; Degree distribution; Algorithm; Machine learning; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001376085,0.0002110417,0.0003164478,0.00008113059,0.003410201,0.000231213,0.0006920454,0.00004611843,0.0000595358],"category_scores_gemma":[0.00001909606,0.0001870222,0.0001434767,0.001756698,0.0005358714,0.0002804678,0.0002704413,0.0008175599,8.138422e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005246312,"about_ca_system_score_gemma":0.000209796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004610464,"about_ca_topic_score_gemma":0.002781996,"domain_scores_codex":[0.9982058,0.0003731835,0.000283513,0.0002827859,0.000335011,0.0005196895],"domain_scores_gemma":[0.998061,0.0003086619,0.0001716273,0.0009152989,0.0004219773,0.0001214089],"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":[0.0004726211,0.0007124947,0.01026713,0.00004223565,0.000204891,0.000001331324,0.002024903,0.7686855,0.04119653,0.02736638,0.002002537,0.1470235],"study_design_scores_gemma":[0.0007516316,0.0001755817,0.002345322,0.00008260837,0.0001496965,0.00000431199,0.0009001612,0.5953511,0.03238889,0.3669,0.000426123,0.000524633],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.514788,0.00001735563,0.4830172,0.00002930352,0.00008083143,0.0002294974,0.00002694812,0.00006557474,0.001745273],"genre_scores_gemma":[0.9832982,0.000001116205,0.01607426,0.00007977418,0.0003383549,0.00004761877,0.0001011579,0.00001602596,0.00004353061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4685102,"threshold_uncertainty_score":0.9978872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02028907242691966,"score_gpt":0.2689334541712341,"score_spread":0.2486443817443144,"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."}}