{"id":"W4252365478","doi":"10.36227/techrxiv.14396390","title":"Competitive Routing on a variant of Delaunay Triangulation","year":2021,"lang":"en","type":"preprint","venue":"","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Delaunay triangulation; Constrained Delaunay triangulation; Bowyer–Watson algorithm; Pitteway triangulation; Ruppert's algorithm; Chew's second algorithm; Minimum-weight triangulation; Computer science; Point set triangulation; Mathematics; Distributed computing; Theoretical computer science; Mathematical optimization; Algorithm","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":[0.001167684,0.0005640161,0.0005885266,0.0008712216,0.0007946259,0.001717224,0.001872716,0.001046999,0.006307863],"category_scores_gemma":[0.004401659,0.0004637966,0.0008313333,0.001291672,0.001259639,0.002341865,0.002374135,0.001141263,0.001431759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001312594,"about_ca_system_score_gemma":0.0008935414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004919641,"about_ca_topic_score_gemma":0.004712889,"domain_scores_codex":[0.9977717,0.0005303388,0.0001085054,0.000378916,0.001040484,0.0001699939],"domain_scores_gemma":[0.9985929,0.0004916535,0.0001156028,0.0003107839,0.0004114321,0.0000775929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001470655,0.00005662646,0.0006023145,0.0002208576,0.00004133838,0.000278065,0.0003985676,0.2415846,0.01481052,0.5927666,0.006963872,0.1421295],"study_design_scores_gemma":[0.00004322391,0.0001605813,0.0002699712,0.00005008039,0.00002771466,0.0004246932,0.0001486947,0.7700391,0.006783039,0.1465418,0.07545568,0.0000553478],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006094187,0.0001757532,0.9811749,0.0001702132,0.00009098108,0.00008089163,0.00005005246,0.0004138281,0.01174917],"genre_scores_gemma":[0.1962763,0.0005699691,0.7897383,0.0002739057,0.0001463964,0.0003322834,0.0002814085,0.0003849818,0.01199647],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006307863,"threshold_uncertainty_score":0.02110195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0177334215943897,"score_gpt":0.2368206128746574,"score_spread":0.2190871912802677,"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."}}