{"id":"W2145427355","doi":"10.1142/s0218195900000115","title":"POINT AND LINE SEGMENT RECONSTRUCTION FROM VISIBILITY INFORMATION","year":2000,"lang":"en","type":"article","venue":"International Journal of Computational Geometry & Applications","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Visibility polygon; Visibility graph; Visibility; Mathematics; Graph; Set (abstract data type); Line segment; Dual graph; Line (geometry); Algorithm; Computer science; Combinatorics; Planar graph; Simple polygon; Geometry; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005189653,0.0001756909,0.0002165239,0.0006141256,0.0001579431,0.0003906154,0.0007052787,0.00007844565,0.0003394688],"category_scores_gemma":[0.0000536378,0.0001771372,0.0001250468,0.000642627,0.00007284396,0.002551882,0.0001037294,0.0002216369,0.0001045153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001572437,"about_ca_system_score_gemma":0.0002011585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001778135,"about_ca_topic_score_gemma":0.000001686668,"domain_scores_codex":[0.9975955,0.00007730188,0.0009938612,0.0002648061,0.0009204334,0.0001480611],"domain_scores_gemma":[0.9972315,0.0003678667,0.0005493668,0.0002119431,0.001475377,0.0001639084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005084893,0.000144946,0.000375769,0.000006170686,0.0001351824,0.000002702734,0.000151655,0.09887744,0.0001013789,0.01446887,0.0002662802,0.8854188],"study_design_scores_gemma":[0.003399633,0.0003635843,0.04570068,0.0001084383,0.00008162775,0.001399508,0.0001507506,0.2346809,0.001409594,0.5357033,0.1762758,0.0007261303],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08583861,0.0003203077,0.9100437,0.002320955,0.0004400822,0.0002778543,0.0000650242,0.00005174163,0.0006417398],"genre_scores_gemma":[0.7522665,0.0002201786,0.2453404,0.0009699251,0.0008453799,0.0000483616,0.0002196909,0.00000827932,0.00008120246],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8846926,"threshold_uncertainty_score":0.7223447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007230949104351661,"score_gpt":0.2539805635127922,"score_spread":0.2467496144084405,"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."}}