{"id":"W2170006979","doi":"10.1007/s10107-010-0349-7","title":"An improved column generation algorithm for minimum sum-of-squares clustering","year":2010,"lang":"en","type":"article","venue":"Mathematical Programming","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":99,"is_retracted":false,"has_abstract":false,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Mathematics; Column (typography); Cluster analysis; Explained sum of squares; Bottleneck; Algorithm; Column generation; Set (abstract data type); Centroid; Point (geometry); Combinatorics; Square (algebra); Euclidean space; Mathematical optimization; Computer science; Statistics; Geometry","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":[0.0007982343,0.0001830071,0.0002846081,0.0001103113,0.0001941197,0.0003413293,0.0008900949,0.0001254233,0.00001133519],"category_scores_gemma":[0.0002824005,0.0001732182,0.00009593284,0.000259758,0.0001207644,0.0005819192,0.0002733115,0.000253938,0.000007288833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003067869,"about_ca_system_score_gemma":0.00005622868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009879556,"about_ca_topic_score_gemma":0.00002223739,"domain_scores_codex":[0.9981113,0.00004290709,0.0004613242,0.0004794059,0.0003579977,0.0005470617],"domain_scores_gemma":[0.9983954,0.0002665358,0.0001320264,0.0007561165,0.0002455004,0.0002043828],"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":[0.000002374328,0.0001681135,0.000002708311,0.0001265005,0.00001060646,0.000002329481,0.0004142698,0.00004901692,0.09746256,0.0021291,0.000006235071,0.8996262],"study_design_scores_gemma":[0.0003709161,0.0003609812,0.000006560077,0.00002221,0.000006081903,0.00001985896,0.00005962951,0.9743242,0.02008656,0.004070641,0.0004745788,0.0001977582],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01208412,0.00001377127,0.9863195,0.0001072954,0.0002807694,0.0009175584,0.000004337287,0.0002283322,0.00004427244],"genre_scores_gemma":[0.1070602,5.661294e-7,0.8922771,0.00001644231,0.0002230279,0.0002939165,0.000007821333,0.000029252,0.00009175244],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9742752,"threshold_uncertainty_score":0.7063631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03302216249232391,"score_gpt":0.335101045809392,"score_spread":0.3020788833170681,"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."}}