{"id":"W2147646759","doi":"10.1145/1822327.1822338","title":"Estimation of the number of cliques in a random graph","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Exponential random graph models; Random graph; Mathematics; Combinatorics; Induced subgraph isomorphism problem; Vertex (graph theory); Clique; Clique graph; Graph; Discrete mathematics; Line graph; Graph power; 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":[0.003796653,0.0008408829,0.00154735,0.004070161,0.0008234284,0.001472828,0.002252472,0.001635438,0.001295455],"category_scores_gemma":[0.04491876,0.0006425771,0.001051108,0.002108503,0.001571535,0.005072338,0.001197348,0.001397913,0.0006048215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009980891,"about_ca_system_score_gemma":0.000814771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00258196,"about_ca_topic_score_gemma":0.002375538,"domain_scores_codex":[0.9974699,0.0008926445,0.0001351609,0.0007150833,0.0006221369,0.0001651014],"domain_scores_gemma":[0.9522134,0.0379708,0.003049767,0.003988456,0.002158292,0.0006192941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004460996,0.0002475751,0.05786449,0.0004742971,0.0002898869,0.0002275555,0.0004582145,0.6556274,0.009662866,0.0650949,0.003899961,0.2057067],"study_design_scores_gemma":[0.00001856364,0.00003930995,0.003212514,0.00002848192,0.00001896409,0.0001307398,0.00006811871,0.9539962,0.003346645,0.03757952,0.001525747,0.00003507742],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04840439,0.0003726796,0.9489064,0.0003027348,0.00002215306,0.00008553894,0.0003082507,0.0008072451,0.0007906666],"genre_scores_gemma":[0.4420926,0.0005656774,0.5545599,0.0001216175,0.0001095663,0.000202131,0.001379388,0.000185956,0.0007832657],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004070161,"threshold_uncertainty_score":0.02007884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00776850519432478,"score_gpt":0.2769016244710873,"score_spread":0.2691331192767626,"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."}}