{"id":"W1636026099","doi":"","title":"Tunneling for triangle strips in continuous level-of-detail meshes","year":2001,"lang":"en","type":"article","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Polygon mesh; STRIPS; Computer science; Set (abstract data type); Triangle mesh; Volume mesh; Topology (electrical circuits); Algorithm; Mesh generation; Computer graphics (images); Mathematics; Engineering; Structural engineering; Combinatorics; Finite element method; Programming language","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":[0.0005447804,0.00008518817,0.0002031474,0.000243745,0.00004154567,0.00006837725,0.0004727571,0.00004677923,0.000009660544],"category_scores_gemma":[0.00004108563,0.00007770688,0.00008063973,0.000553392,0.00001552009,0.0002096221,0.0001033216,0.00005108882,7.445834e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000108949,"about_ca_system_score_gemma":0.0000365485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007897648,"about_ca_topic_score_gemma":0.00007370136,"domain_scores_codex":[0.9991211,0.00003757912,0.000336453,0.0002213132,0.0001161029,0.0001674727],"domain_scores_gemma":[0.9993277,0.0001694835,0.00008659997,0.0002561172,0.0001251689,0.0000349928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001000114,0.0001138423,0.004100077,0.00001527655,0.000008906087,0.000003501179,0.0003104163,0.00001763567,0.0003617232,0.93032,0.001376864,0.06336177],"study_design_scores_gemma":[0.00266711,0.0006303231,0.006187668,0.0001226136,0.000008609648,0.00001645864,0.0001519198,0.8093039,0.06147171,0.08132315,0.03752506,0.0005914178],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0148492,0.00009038549,0.9836356,0.0001710412,0.0001100407,0.0002506754,0.000003019924,0.0001585653,0.0007314733],"genre_scores_gemma":[0.912963,0.00005914564,0.08640745,0.0001531593,0.00002944561,0.00002585353,0.000002428243,0.000006672371,0.0003528828],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8981138,"threshold_uncertainty_score":0.3168795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1251142838020767,"score_gpt":0.3350788334560725,"score_spread":0.2099645496539958,"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."}}