{"id":"W2969438042","doi":"10.1007/978-3-030-35802-0_2","title":"Representing Graphs and Hypergraphs by Touching Polygons in 3D","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Regular polygon; Vertex (graph theory); Graph; Point (geometry); Enhanced Data Rates for GSM Evolution; Graph drawing; Construct (python library); Time complexity","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":[0.0008100909,0.0003425667,0.0003841862,0.001130292,0.0002153599,0.0007065291,0.001274508,0.0002115004,0.000008427552],"category_scores_gemma":[0.00008936745,0.0003691523,0.00007649828,0.0009794023,0.0002417003,0.000731778,0.0009727888,0.0006233035,0.000009602001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009548156,"about_ca_system_score_gemma":0.0002891206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001054259,"about_ca_topic_score_gemma":0.0001849143,"domain_scores_codex":[0.996878,0.00004146301,0.0004612978,0.00145168,0.0006771422,0.0004904481],"domain_scores_gemma":[0.9983888,0.0004835416,0.0002026431,0.0007024467,0.000107328,0.0001152715],"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":[0.000004156685,0.00003504744,0.001362514,0.00004318644,0.00001113082,0.00005336478,0.000643103,0.073745,0.000960547,0.03073302,0.0000755891,0.8923333],"study_design_scores_gemma":[0.0003750788,0.00009369097,0.001210808,0.0003548211,0.000005388174,0.0001161507,3.157585e-7,0.8293495,0.0005780964,0.1658981,0.00131198,0.0007059815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005382402,0.00154146,0.9890015,0.00044956,0.001098404,0.0003056384,0.000004238804,0.00008435681,0.002132488],"genre_scores_gemma":[0.6445352,0.0002160199,0.3520407,0.001669753,0.0002086025,0.000009162305,0.00002230651,0.00003959811,0.001258625],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8916274,"threshold_uncertainty_score":0.999876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01022786060510172,"score_gpt":0.2329833352907458,"score_spread":0.2227554746856441,"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."}}