{"id":"W2149884111","doi":"","title":"Computing Nice Sweeps for Polyhedra and Polygons","year":2004,"lang":"en","type":"article","venue":"Canadian Conference on Computational Geometry","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Polyhedron; Monotone polygon; Combinatorics; Regular polygon; Polygon (computer graphics); Mathematics; Rectilinear polygon; Simple polygon; Convex polygon; Convex set; Polygon covering; Krein–Milman theorem; Convex polytope; Computer science; Geometry; Convex optimization","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002837602,0.0002329645,0.0002130559,0.0008371538,0.0005611164,0.0005039274,0.0004744167,0.0001046397,0.00002234078],"category_scores_gemma":[0.0001735885,0.000264003,0.00007329984,0.0008575887,0.00007523085,0.0004499404,0.00007588167,0.0001732839,0.00005563318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002349125,"about_ca_system_score_gemma":0.001629828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001705321,"about_ca_topic_score_gemma":0.002335955,"domain_scores_codex":[0.9982315,0.0000370656,0.0003102823,0.000609008,0.0003294119,0.0004827648],"domain_scores_gemma":[0.9982468,0.0004445725,0.0001079442,0.0002433314,0.0003955752,0.0005617658],"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":[0.000006173467,0.00003061606,0.00008947203,0.00001444599,0.00002380174,0.000008179873,0.0001950317,0.1168613,0.0000517458,0.8296044,0.0003603975,0.05275434],"study_design_scores_gemma":[0.002629525,0.0005565732,0.03587692,0.0001348553,0.00002193716,0.0001416918,0.0001455368,0.6357786,0.0003944789,0.3145851,0.008680854,0.001053939],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05836974,0.0001444065,0.92965,0.00874744,0.0005221806,0.0003519835,0.00008242012,0.0001102549,0.002021534],"genre_scores_gemma":[0.8975875,0.000005305407,0.09885318,0.00311163,0.0001693905,0.0000155322,0.0001319824,0.00001358151,0.0001119444],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8392177,"threshold_uncertainty_score":0.9999812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02848420590755417,"score_gpt":0.2638921882300127,"score_spread":0.2354079823224585,"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."}}