{"id":"W2091292848","doi":"10.1016/s0031-3203(99)00216-2","title":"J-Means: a new local search heuristic for minimum sum of squares clustering","year":2001,"lang":"en","type":"article","venue":"Pattern Recognition","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":257,"is_retracted":false,"has_abstract":false,"ca_institutions":"Group for Research in Decision Analysis","funders":"","keywords":"Local search (optimization); Heuristic; Heuristics; Cluster analysis; Degeneracy (biology); Metaheuristic; Mathematical optimization; Variable neighborhood search; Mathematics; Local optimum; Centroid; Guided Local Search; Explained sum of squares; Algorithm; Computer science; Artificial intelligence; Statistics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002556557,0.0001205625,0.0001397831,0.0002014291,0.00007664517,0.00006348315,0.0001237127,0.00004073613,0.0009902482],"category_scores_gemma":[0.00006115314,0.0001270808,0.00008230426,0.0002188937,0.00002790231,0.0003577511,0.00006915529,0.00005183719,0.0004614187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002356353,"about_ca_system_score_gemma":0.00001090654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002865323,"about_ca_topic_score_gemma":0.002005435,"domain_scores_codex":[0.9990172,0.000009524514,0.0003152933,0.0002296103,0.0001974493,0.0002308817],"domain_scores_gemma":[0.9995686,0.00002707361,0.00006041195,0.0001453109,0.0001817736,0.00001676348],"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":[0.0001567083,0.0001733042,0.006228048,0.001429632,0.00004338257,0.00000339489,0.0001673168,0.001893646,0.0002131578,0.00005547027,0.006785854,0.9828501],"study_design_scores_gemma":[0.003468541,0.0001303676,0.02253531,0.0005435972,0.0002336022,0.000003747623,0.003007229,0.9043666,0.0006005681,0.004571517,0.05971128,0.0008276894],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2643189,0.00003421215,0.7308247,0.001098376,0.000453137,0.0005111155,0.0000142969,0.0000811109,0.002664082],"genre_scores_gemma":[0.9976753,0.00002784503,0.000232665,0.0008001807,0.0005205904,0.00004469782,0.0002773221,0.00001834519,0.0004030778],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9820224,"threshold_uncertainty_score":0.999923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0745715607572284,"score_gpt":0.2737845802329744,"score_spread":0.199213019475746,"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."}}