{"id":"W2951184112","doi":"10.22215/etd/2018-13352","title":"Implementation of Minimum Edge Constraints Sets for Proximity Graphs","year":2018,"lang":"en","type":"dissertation","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Delaunay triangulation; Computer science; Edge contraction; Enhanced Data Rates for GSM Evolution; Graph; Spanning tree; Constrained Delaunay triangulation; Line graph; Theoretical computer science; Algorithm; Mathematics; Combinatorics; Voltage graph; Artificial intelligence","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":[0.001057389,0.0007247788,0.0006453324,0.001385017,0.0009308454,0.001983155,0.002402495,0.0009295307,0.007130153],"category_scores_gemma":[0.01242106,0.0005931067,0.0007110185,0.002542089,0.000516272,0.002742193,0.002246958,0.001309053,0.001747516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001021416,"about_ca_system_score_gemma":0.001830796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003667613,"about_ca_topic_score_gemma":0.005468896,"domain_scores_codex":[0.9976814,0.0004232186,0.0002218808,0.0003189238,0.001228197,0.0001263082],"domain_scores_gemma":[0.9956865,0.001435215,0.000206766,0.001612131,0.0009484615,0.0001108633],"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":[0.0004368458,0.000336636,0.002120945,0.0005643614,0.0001235901,0.0001999446,0.0006435149,0.1896376,0.02502775,0.06750442,0.01817378,0.6952305],"study_design_scores_gemma":[0.0001218186,0.0001817621,0.0009754068,0.00007727343,0.0000272803,0.0003272049,0.0002720954,0.8603213,0.05164547,0.0587301,0.02725461,0.00006559776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0249333,0.0001845258,0.9636121,0.0001897659,0.0000625281,0.0002406682,0.0006565478,0.005539527,0.004581039],"genre_scores_gemma":[0.1460363,0.0001955621,0.8490335,0.00008217804,0.00002048544,0.0003100274,0.001971488,0.0004763292,0.001874078],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.007130153,"threshold_uncertainty_score":0.02385271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0256196682222631,"score_gpt":0.3309451819244595,"score_spread":0.3053255137021965,"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."}}