{"id":"W7018028875","doi":"","title":"CHAN's PLANAR CONVEX HULL ALGORITHM: A Brief Survey and Sequential Experimental Comparison","year":2006,"lang":"en","type":"article","venue":"NPARC","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convex hull; Planar; Hull; Convex set; Correctness; Set (abstract data type); Regular polygon","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002093152,0.0001643359,0.0002276139,0.00006094418,0.0001788125,0.0002257466,0.0004671192,0.00007036181,0.00006484435],"category_scores_gemma":[0.000005423,0.0001523211,0.00003135185,0.0001397541,0.00007912703,0.0004028249,0.0003256963,0.0001224471,0.0000214053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002161176,"about_ca_system_score_gemma":0.0000329984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001183392,"about_ca_topic_score_gemma":0.00003839736,"domain_scores_codex":[0.9986023,0.0001121802,0.0002289238,0.0004482823,0.0003104296,0.0002978373],"domain_scores_gemma":[0.9993305,0.00006137718,0.00008394118,0.0003840415,0.00003175327,0.0001083904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001512227,0.002243835,0.02375734,0.00005952453,0.0001250717,0.0004204526,0.003051604,0.00006300137,0.3412183,0.07644097,0.2548279,0.2976408],"study_design_scores_gemma":[0.002823305,0.0004620112,0.05800162,0.00004725793,0.00001001094,0.0001285433,0.0001090731,0.801285,0.1060724,0.00427748,0.02582492,0.0009584628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09364005,0.0005485223,0.8998337,0.0002078417,0.0007523221,0.0002431916,0.0001305005,0.0002312393,0.004412638],"genre_scores_gemma":[0.9000725,0.000007741945,0.09926492,0.0001406559,0.0002014804,0.00001181545,0.000143862,0.00001161406,0.000145471],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8064324,"threshold_uncertainty_score":0.6211473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02496564069630522,"score_gpt":0.2719063722001711,"score_spread":0.2469407315038658,"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."}}