{"id":"W4220735151","doi":"10.26599/tst.2021.9010051","title":"Approximation Algorithm for the Balanced 2-Correlation Clustering Problem","year":2022,"lang":"en","type":"article","venue":"Tsinghua Science & Technology","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"China Postdoctoral Science Foundation; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Cluster analysis; Vertex (graph theory); Similarity (geometry); Partition (number theory); Series (stratigraphy); Set (abstract data type); Algorithm; Computer science; Combinatorics; Mathematics; Artificial intelligence; Graph","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0007219869,0.00009515828,0.0001210106,0.0003896372,0.001472435,0.00006401193,0.0006920801,0.00002118362,0.00008396319],"category_scores_gemma":[0.000008451314,0.00008039804,0.00005584191,0.002193479,0.0003602305,0.0001530202,0.0004258874,0.0002091412,0.000003060608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001345782,"about_ca_system_score_gemma":0.00008010474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004017912,"about_ca_topic_score_gemma":0.000002493944,"domain_scores_codex":[0.9989238,0.00001699134,0.0001965249,0.0003177573,0.0002314593,0.0003134164],"domain_scores_gemma":[0.9993213,0.00005453863,0.0001665461,0.0003584106,0.00008074618,0.00001840112],"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":[0.000003576584,0.00004726839,0.001623996,0.000001932502,0.00001492571,1.314982e-7,0.0002300586,0.01365402,0.00603047,0.05402075,0.0002759664,0.9240969],"study_design_scores_gemma":[0.0001405225,0.00005965428,0.0001105493,0.000004049346,0.00001971039,0.000003000584,0.0006802873,0.9345064,0.002512882,0.05398086,0.007870701,0.0001113962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006414847,0.00003485226,0.9905484,0.0009985475,0.0001150231,0.0005569078,0.000005992114,0.0002686255,0.001056849],"genre_scores_gemma":[0.9128327,5.845792e-7,0.08628104,0.00003297584,0.00006430835,0.0006087099,0.00001202469,0.000009411632,0.0001582911],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9239855,"threshold_uncertainty_score":0.9998275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01066192649364501,"score_gpt":0.2645979031093727,"score_spread":0.2539359766157277,"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."}}