{"id":"W2059822086","doi":"10.1109/tfuzz.2012.2236842","title":"Proximity-Based Clustering: A Search for Structural Consistency in Data With Semantic Blocks of Features","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Fuzzy Systems","topic":"Modeling, Simulation, and Optimization","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Cluster analysis; Partition (number theory); Computer science; Semantics (computer science); Series (stratigraphy); Consistency (knowledge bases); Class (philosophy); Block (permutation group theory); Theoretical computer science; Data mining; Mathematics; Algorithm; Artificial intelligence; Combinatorics","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":[0.00030592,0.0001716614,0.0003276062,0.0002292341,0.0001271251,0.000060396,0.0002231976,0.0001144153,0.00001624277],"category_scores_gemma":[0.00001495827,0.0001372568,0.00004995828,0.0002184949,0.00005006742,0.0002500848,0.000001727329,0.0001480784,0.000001700005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004888781,"about_ca_system_score_gemma":0.0001214528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006997157,"about_ca_topic_score_gemma":0.001049132,"domain_scores_codex":[0.9986028,0.00009353716,0.0004722748,0.0003161052,0.0002963699,0.000218904],"domain_scores_gemma":[0.998499,0.0003503636,0.0001418014,0.0006545483,0.0002969588,0.00005730489],"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":[0.0001487901,0.0001342362,0.0001948403,0.001283098,0.00005934888,7.333298e-7,0.0007551051,0.9964778,0.0002000154,0.0002901922,0.0001160971,0.0003397156],"study_design_scores_gemma":[0.001472364,0.0001366113,0.00006028982,0.0003495415,0.00006754898,0.000008819559,0.0004028325,0.9961252,0.0008394814,0.0003606396,0.00000826811,0.0001684058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.139774,0.00003187253,0.857397,0.00007331069,0.0002082069,0.002204264,0.000113902,0.00005807311,0.0001393686],"genre_scores_gemma":[0.9813144,0.000002910959,0.01811813,0.00001130113,0.00003155234,0.000157743,0.00003511546,0.00003344655,0.0002953516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8415405,"threshold_uncertainty_score":0.5597171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06965385089781989,"score_gpt":0.3125924315325785,"score_spread":0.2429385806347586,"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."}}