{"id":"W1545136458","doi":"10.1007/978-3-642-14031-0_50","title":"On the Computation of 3D Visibility Skeletons","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria; McGill University","funders":"","keywords":"Visibility; Set (abstract data type); Skeleton (computer programming); Computation; Computer science; Rest (music); Data structure; Theoretical computer science; Visibility graph; Algorithm; Artificial intelligence; Mathematics; Geography; Geometry","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":[0.0004308774,0.000199414,0.0002497184,0.0002421198,0.00008787498,0.00005066113,0.0004973548,0.0001652071,0.00002757352],"category_scores_gemma":[0.00005718961,0.0001415148,0.00008594084,0.000200184,0.0003085774,0.00004134221,0.00007704604,0.000675595,0.00001353583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005809703,"about_ca_system_score_gemma":0.00005223454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001068982,"about_ca_topic_score_gemma":0.00005612481,"domain_scores_codex":[0.9988509,0.0000100385,0.0002584963,0.0003402066,0.0003618157,0.0001785865],"domain_scores_gemma":[0.9989637,0.000376628,0.00006458422,0.0004669259,0.00009169132,0.00003648394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[6.942321e-7,0.000005054926,0.000005141987,0.00001858544,0.000007658817,0.000001098783,0.0001352926,0.8852204,0.0003132401,0.0004987274,0.00000368605,0.1137904],"study_design_scores_gemma":[0.00003644447,0.0000232309,0.00002514581,0.0001228595,0.000009376394,0.000001280253,5.742697e-8,0.9351705,0.001258687,0.0631851,0.00002603601,0.0001412819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005292387,0.00007931241,0.991829,0.0001350559,0.000422778,0.00009783966,0.000005152152,0.00006690028,0.002071615],"genre_scores_gemma":[0.972267,0.000008441229,0.02742673,0.0001416588,0.0001083044,0.000001409402,0.000003019639,0.00001759194,0.00002586104],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9669746,"threshold_uncertainty_score":0.5770805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01259578119881716,"score_gpt":0.2304028464435537,"score_spread":0.2178070652447366,"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."}}