{"id":"W2127816126","doi":"10.1145/2907052","title":"Better Balance by Being Biased","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Toronto","funders":"","keywords":"Approximation algorithm; Conjecture; Combinatorics; Mathematics; Constraint (computer-aided design); Discrete mathematics","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":[0.0001825771,0.0002281778,0.0001938066,0.000176769,0.0003382093,0.0001202366,0.001513664,0.00009243059,0.0002116606],"category_scores_gemma":[0.00002550189,0.0001720075,0.0001585963,0.0005398084,0.0001162157,0.0006240949,0.00002910142,0.0002131477,0.0003033053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006140026,"about_ca_system_score_gemma":0.00003069379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002464575,"about_ca_topic_score_gemma":0.000004222102,"domain_scores_codex":[0.9982489,0.0000696073,0.0002593265,0.0005898609,0.0003844521,0.000447857],"domain_scores_gemma":[0.9980428,0.0003849808,0.00005868698,0.001296212,0.00006006692,0.0001572705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000004629427,0.0001432442,0.00004348034,0.000003593905,0.00003330399,0.00001090723,0.00009262047,0.000008340203,0.002342495,0.001302664,0.001398683,0.994616],"study_design_scores_gemma":[0.008835967,0.001539794,0.00520379,0.0006730478,0.0001029286,0.000248009,0.0000817307,0.0762827,0.2896279,0.3477734,0.2656777,0.003953007],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002158253,0.00004000579,0.9843125,0.01151429,0.0008173372,0.0001291512,0.00005459107,0.0004260488,0.0005478132],"genre_scores_gemma":[0.4734235,0.0001660093,0.5198901,0.003705116,0.0001979689,0.0001108532,0.000004629739,0.00004522051,0.002456579],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9906631,"threshold_uncertainty_score":0.7014263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01799228803662961,"score_gpt":0.2423846366341022,"score_spread":0.2243923485974726,"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."}}