{"id":"W2107749697","doi":"10.1142/s0218195911003627","title":"RECONSTRUCTING CONVEX POLYGONS AND CONVEX POLYHEDRA FROM EDGE AND FACE COUNTS IN ORTHOGONAL PROJECTIONS","year":2011,"lang":"en","type":"article","venue":"International Journal of Computational Geometry & Applications","topic":"Digital Image Processing Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Polyhedron; Mathematics; Regular polygon; Combinatorics; Polygon (computer graphics); Rectilinear polygon; Convex polygon; Star-shaped polygon; Face (sociological concept); Enhanced Data Rates for GSM Evolution; Convex polytope; Polygon covering; Convex set; Geometry; Convex optimization; Computer science; Simple polygon; 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":[0.00105886,0.00140271,0.002002511,0.001514248,0.0007738966,0.001797761,0.001719192,0.001381457,0.002212086],"category_scores_gemma":[0.00845592,0.001597128,0.001559308,0.002489749,0.001649456,0.003419547,0.002293001,0.002552835,0.0006252254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007645065,"about_ca_system_score_gemma":0.0008724112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003607204,"about_ca_topic_score_gemma":0.003830594,"domain_scores_codex":[0.9985563,0.0003456525,0.00008696995,0.000334435,0.0004905699,0.0001859846],"domain_scores_gemma":[0.9948192,0.003456141,0.0005312784,0.0006155552,0.0003990084,0.000178784],"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":[0.0004565296,0.0001841604,0.003625935,0.0003595524,0.00006746918,0.0004922107,0.0003179151,0.7541073,0.008641381,0.0440414,0.00334393,0.1843622],"study_design_scores_gemma":[0.00002415461,0.00005868864,0.0005348624,0.00002365349,0.00001215147,0.0001804693,0.0001310832,0.9493486,0.004678471,0.04380509,0.001176944,0.00002578664],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06078024,0.0001847809,0.9365366,0.0001709676,0.0000215509,0.00008039749,0.0003600212,0.0003322457,0.001533103],"genre_scores_gemma":[0.2342231,0.000365638,0.7617613,0.00005761163,0.00005352253,0.0002396566,0.001611408,0.0001866585,0.00150102],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003607204,"threshold_uncertainty_score":0.007400155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02341584738390962,"score_gpt":0.2816587234734539,"score_spread":0.2582428760895443,"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."}}