{"id":"W1976011284","doi":"10.1007/s00224-007-9085-7","title":"A Randomized Algorithm for Online Unit Clustering","year":2007,"lang":"en","type":"article","venue":"Theory of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Competitive analysis; Online algorithm; Randomized algorithm; Cluster analysis; Partition (number theory); Upper and lower bounds; Extension (predicate logic); Computer science; Set (abstract data type); Mathematics; Combinatorics; Unit (ring theory); Algorithm; Artificial intelligence","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":[0.009720013,0.0001225452,0.0004702277,0.0001873964,0.0001151214,0.00007713279,0.0006015002,0.00005411366,0.000002160137],"category_scores_gemma":[0.0001716786,0.0001048349,0.000124032,0.0003077662,0.0000900528,0.0001117018,0.0001679112,0.00008661789,0.000003286844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002044963,"about_ca_system_score_gemma":0.00004112185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001563032,"about_ca_topic_score_gemma":0.000001423307,"domain_scores_codex":[0.9981464,0.0004444864,0.0006319733,0.0002219775,0.0002378714,0.0003173499],"domain_scores_gemma":[0.9968175,0.002218103,0.0002870994,0.0003253452,0.0002678426,0.00008411201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001804179,0.0001489649,0.000007124111,0.0002936435,0.0001367808,0.000004659466,0.003795879,0.07001206,0.0001785031,0.5505238,0.00006368354,0.3730307],"study_design_scores_gemma":[0.02596869,0.00004934861,0.000008433529,0.0001447606,0.000006654476,0.00001386503,0.0001400174,0.9699624,0.0001040875,0.003109617,0.0003774452,0.0001147478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002237346,0.0001917936,0.9945263,0.0000464123,0.0006976996,0.0008611016,0.000003774213,0.0001941063,0.001241423],"genre_scores_gemma":[0.4292733,0.000005109,0.5697158,0.00008884825,0.0002034775,0.000006966501,0.000008474633,0.00001726519,0.0006807377],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8999503,"threshold_uncertainty_score":0.4275042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04092833779722757,"score_gpt":0.3136730632364606,"score_spread":0.272744725439233,"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."}}