{"id":"W4234482552","doi":"10.1002/widm.16","title":"Rough clustering","year":2011,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Cluster analysis; Rough set; Computer science; Fuzzy clustering; Data mining; Similarity (geometry); Artificial intelligence; Self-organizing map; Set (abstract data type); Pattern recognition (psychology); Image (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":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0009629118,0.0003424989,0.0005436946,0.0001146433,0.0003610189,0.0003718417,0.002627707,0.00008422146,0.00002630784],"category_scores_gemma":[0.00006132058,0.0002548124,0.0001064717,0.0003222053,0.0001281215,0.003487237,0.01250185,0.000177746,0.0001543595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002624538,"about_ca_system_score_gemma":0.00005418567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009504374,"about_ca_topic_score_gemma":0.00007039245,"domain_scores_codex":[0.9976039,0.0001816688,0.0006203306,0.001041831,0.0001172639,0.0004350414],"domain_scores_gemma":[0.9972286,0.00008137678,0.0001983866,0.002307031,0.00002838138,0.0001561891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002820454,0.0002628611,0.0009639052,0.000318449,0.00004784499,0.00006739028,0.01863318,5.242906e-7,0.00002258898,0.001612975,0.04680566,0.9312364],"study_design_scores_gemma":[0.003047673,0.002576835,0.01285156,0.01506655,0.0004555524,0.001862843,0.00616149,0.3208404,0.000123826,0.01055238,0.6206754,0.005785407],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01779968,0.1861961,0.535041,0.0006056209,0.005086207,0.001287129,0.0002345408,0.0005721884,0.2531775],"genre_scores_gemma":[0.633905,0.03145389,0.3283932,0.000691792,0.001275433,0.0001904744,0.000515378,0.0001096084,0.003465259],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.925451,"threshold_uncertainty_score":0.9999904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1580328407861034,"score_gpt":0.3397054162188211,"score_spread":0.1816725754327177,"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."}}