{"id":"W2561495450","doi":"10.4230/lipics.socg.2015.141","title":"1-String B_2-VPG Representation of Planar Graphs","year":2015,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Planar; Planar graph; String (physics); Combinatorics; Representation (politics); Graph; Enhanced Data Rates for GSM Evolution; Mathematics; Grid; Computer science; Topology (electrical circuits); Geometry; Artificial intelligence; Computer graphics (images)","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":[0.000319547,0.0005557315,0.0004487958,0.0009424997,0.0005047606,0.001655819,0.0009515532,0.0009886764,0.01096281],"category_scores_gemma":[0.001966506,0.0003080404,0.0005300791,0.001390045,0.0008624602,0.002607178,0.001659661,0.001602915,0.003140669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004720501,"about_ca_system_score_gemma":0.0003441889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007526277,"about_ca_topic_score_gemma":0.0005174942,"domain_scores_codex":[0.9994702,0.00009796843,0.00003209277,0.0001180452,0.0001856699,0.00009609141],"domain_scores_gemma":[0.9994143,0.0001469617,0.00008043594,0.0001760552,0.0001421027,0.00004010706],"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":[0.0002224807,0.00008003496,0.0006108849,0.0002305254,0.00001923022,0.000403979,0.0003843098,0.03208849,0.01341771,0.8066962,0.01219646,0.1336497],"study_design_scores_gemma":[0.00004371224,0.0001102161,0.0004243503,0.00006517635,0.00002726358,0.0004776994,0.0002500877,0.1423665,0.008113807,0.8108444,0.03724189,0.00003482266],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05559336,0.0001847172,0.9151101,0.0004737999,0.0001325209,0.00009202708,0.0009644506,0.001685555,0.02576349],"genre_scores_gemma":[0.561402,0.0005369721,0.4172447,0.0004312601,0.0001163234,0.0003278289,0.003327919,0.0006892328,0.01592369],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01096281,"threshold_uncertainty_score":0.03667426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04353341120342063,"score_gpt":0.287241074643325,"score_spread":0.2437076634399044,"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."}}