{"id":"W2028768445","doi":"10.1109/ifsa-nafips.2013.6608463","title":"A granular recursive fuzzy meta-clustering algorithm for social networks","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Cluster analysis; Fuzzy clustering; Data mining; Computer science; Fuzzy logic; FLAME clustering; Artificial intelligence; Canopy clustering algorithm","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":[],"consensus_categories":[],"category_scores_codex":[0.0003642439,0.0002505383,0.0003962694,0.0001255906,0.0003964508,0.0003923471,0.001213229,0.0001196785,0.00008360178],"category_scores_gemma":[0.00004134432,0.0002106065,0.0002876526,0.0004375044,0.00007564029,0.000983408,0.0007307503,0.0002380928,0.0000854335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009342592,"about_ca_system_score_gemma":0.00003921194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001038399,"about_ca_topic_score_gemma":0.000009773805,"domain_scores_codex":[0.9977591,0.00008142481,0.0002987108,0.0006238378,0.0003995317,0.0008374169],"domain_scores_gemma":[0.9986439,0.000230433,0.00008674244,0.0004992094,0.0003589151,0.0001807481],"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":[0.00000338908,0.000041632,0.000001463629,0.00001653605,0.0002114878,0.000009350934,0.0003302996,0.002844676,0.00008405036,0.004511169,0.00384342,0.9881025],"study_design_scores_gemma":[0.0004542436,0.0001025479,0.00005518347,0.000004090629,0.0000391762,0.00001644784,0.00005300127,0.9792076,0.0002392667,0.01634639,0.003195573,0.0002864639],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00003532472,0.0001877162,0.9951946,0.001725768,0.0003530505,0.0009009394,0.000004053502,0.0003225851,0.001275992],"genre_scores_gemma":[0.004279439,0.0000156841,0.9909006,0.0005060301,0.0004119719,0.001001226,0.000006156941,0.0000368968,0.002842001],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.987816,"threshold_uncertainty_score":0.8588284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0494273831076943,"score_gpt":0.3102288841149434,"score_spread":0.2608015010072491,"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."}}