{"id":"W2952903853","doi":"10.48550/arxiv.1206.0514","title":"Simultaneous Embeddings with Vertices Mapping to Pre-Specified Points","year":2012,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Combinatorics; Planar graph; Mathematics; Vertex (graph theory); Piecewise linear function; Embedding; Planar; Upper and lower bounds; Piecewise; Book embedding; Random graph; Graph; Discrete mathematics; 1-planar graph; Geometry; Chordal graph; Computer science; Mathematical analysis","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":[0.00108657,0.001497608,0.001034675,0.0005976073,0.0008143228,0.001054424,0.002106133,0.001666236,0.00520331],"category_scores_gemma":[0.009452291,0.0009177134,0.001202259,0.001285507,0.001473795,0.004333744,0.003125679,0.002071389,0.001140189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009073638,"about_ca_system_score_gemma":0.0005228342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001014495,"about_ca_topic_score_gemma":0.001560699,"domain_scores_codex":[0.9983669,0.0003850965,0.0001002622,0.0004745951,0.0004099116,0.0002632898],"domain_scores_gemma":[0.9955506,0.001661003,0.0006438681,0.001738154,0.0002427138,0.000163663],"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":[0.000868416,0.0002566036,0.003911336,0.0002815343,0.0001167205,0.0006033532,0.0004126382,0.6975662,0.03516496,0.113546,0.002764657,0.1445077],"study_design_scores_gemma":[0.0001052816,0.0005439506,0.001287518,0.0000587841,0.00007120363,0.0005818211,0.0003522967,0.8243367,0.04357643,0.118872,0.01014542,0.00006856989],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1408437,0.0001672416,0.8520452,0.0003636379,0.00005999055,0.0001393702,0.0002636603,0.0006006981,0.005516415],"genre_scores_gemma":[0.6710809,0.0003300325,0.3215639,0.0001190454,0.00004303002,0.0002974827,0.0006098236,0.0002262719,0.005729484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00520331,"threshold_uncertainty_score":0.01740682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06647366577109444,"score_gpt":0.1966667355096468,"score_spread":0.1301930697385523,"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."}}