{"id":"W1588217500","doi":"10.37236/2639","title":"Metric Dimension for Random Graphs","year":2013,"lang":"en","type":"article","venue":"The Electronic Journal of Combinatorics","topic":"Graph Labeling and Dimension Problems","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Microsoft Research; National Science Foundation","keywords":"Metric dimension; Combinatorics; Mathematics; Vertex (graph theory); Dimension (graph theory); Packing dimension; Graph; Discrete mathematics; Metric (unit); Random graph; Minkowski–Bouligand dimension; Chordal graph; 1-planar graph","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002234725,0.001073758,0.001501782,0.003357992,0.001560558,0.003634191,0.001287622,0.001472272,0.00275329],"category_scores_gemma":[0.01511896,0.0005353714,0.0008535144,0.002720976,0.003530754,0.005892543,0.002459012,0.002355356,0.0004149776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0026384,"about_ca_system_score_gemma":0.0005565136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001101192,"about_ca_topic_score_gemma":0.0007067419,"domain_scores_codex":[0.9974446,0.001177143,0.0001156498,0.0004999978,0.0004868126,0.0002757796],"domain_scores_gemma":[0.9838594,0.01095264,0.001554233,0.001493032,0.0009094105,0.001231239],"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":[0.00007883496,0.00002833626,0.00173745,0.0001610007,0.00006223602,0.00006013484,0.0002077532,0.01439374,0.001014554,0.9702899,0.0037782,0.008187843],"study_design_scores_gemma":[0.00001557403,0.00003948779,0.001334646,0.00003656453,0.00002146592,0.0001615544,0.00008775867,0.05252695,0.0004507027,0.9394442,0.005848685,0.00003231539],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4119771,0.01842133,0.5102054,0.007709044,0.000429315,0.000185208,0.003659169,0.0005172126,0.0468962],"genre_scores_gemma":[0.9388409,0.005479979,0.04835487,0.0006961502,0.0007507964,0.0003080313,0.001404856,0.0001516132,0.004012864],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003634191,"threshold_uncertainty_score":0.01914304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006990342412215714,"score_gpt":0.2153006784157689,"score_spread":0.2083103360035532,"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."}}