{"id":"W2077735330","doi":"10.1007/s00454-012-9417-5","title":"Approximation Algorithms for Maximum Independent Set of Pseudo-Disks","year":2012,"lang":"en","type":"article","venue":"Discrete & Computational Geometry","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":131,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Rounding; Approximation algorithm; Set (abstract data type); Independent set; Combinatorics; Algorithm; Plane (geometry); Relaxation (psychology); Linear programming relaxation; Set packing; Discrete mathematics; Linear programming; Computer science; Geometry; Graph","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003918263,0.00241582,0.003267406,0.002900626,0.001439438,0.003886797,0.00747471,0.003210488,0.009539285],"category_scores_gemma":[0.02948612,0.001959443,0.002628915,0.005033333,0.002161455,0.007089947,0.006274132,0.005702548,0.002185082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003433702,"about_ca_system_score_gemma":0.002329979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00285183,"about_ca_topic_score_gemma":0.003351307,"domain_scores_codex":[0.9969904,0.001261808,0.0001586173,0.000443564,0.0008731766,0.0002723231],"domain_scores_gemma":[0.9862794,0.009956959,0.0004989268,0.001725174,0.001018567,0.0005209208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00054613,0.0002319761,0.0007613712,0.000590838,0.000160456,0.00008249648,0.0003074505,0.6392685,0.0009997018,0.2323533,0.01312521,0.1115726],"study_design_scores_gemma":[0.00005198746,0.00002733205,0.00008143929,0.00003297875,0.00002153771,0.00003335725,0.00003476977,0.8704271,0.0003745443,0.1274778,0.001425179,0.00001198293],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00784892,0.0008000635,0.9852704,0.0004734094,0.0001435991,0.0001058277,0.0002587551,0.0004639469,0.004635078],"genre_scores_gemma":[0.1892964,0.001205308,0.7994962,0.0003424931,0.0003349085,0.0006854766,0.001321295,0.0006345683,0.006683321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009539285,"threshold_uncertainty_score":0.03191203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03693149263006409,"score_gpt":0.3046274523030603,"score_spread":0.2676959596729963,"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."}}