{"id":"W2809912216","doi":"10.1111/cgf.13592","title":"Solid Geometry Processing on Deconstructed Domains","year":2018,"lang":"en","type":"preprint","venue":"Computer Graphics Forum","topic":"Computational Geometry and Mesh Generation","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Connaught Fund; Adobe Systems","keywords":"Discretization; Geometry processing; Tetrahedron; Geometry; Boundary (topology); Complex geometry; Convergence (economics); Differential geometry; Solid geometry; Variety (cybernetics); Computer science; Finite element method; Mathematics; Mathematical analysis; Artificial intelligence; Polygon mesh; Engineering; Structural engineering","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":[0.001103306,0.0006693549,0.0007197607,0.001106901,0.0004893111,0.001629539,0.001335442,0.001233488,0.005827695],"category_scores_gemma":[0.004120367,0.0004745913,0.0009299257,0.0008159668,0.001779735,0.00151781,0.002700853,0.001645639,0.001155842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007729193,"about_ca_system_score_gemma":0.0008566575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00183272,"about_ca_topic_score_gemma":0.001477461,"domain_scores_codex":[0.9991153,0.0002091254,0.00005035647,0.0001567287,0.0003994045,0.00006913972],"domain_scores_gemma":[0.9975376,0.001115342,0.0002093968,0.0006617755,0.0003543241,0.0001215213],"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":[0.00008323073,0.00006001726,0.001239775,0.00009878023,0.00002684179,0.000212589,0.0003163391,0.8882659,0.01543403,0.04667914,0.001225127,0.04635825],"study_design_scores_gemma":[0.000007068806,0.00002007386,0.0001574044,0.000007609477,0.00000207126,0.00004187963,0.00003827933,0.9815196,0.00311053,0.01351002,0.001579579,0.000005820794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07054632,0.00008800836,0.9231471,0.0001879801,0.00005406614,0.00008101882,0.0000950556,0.0006585713,0.005141827],"genre_scores_gemma":[0.4964072,0.0001018145,0.4965192,0.0001537889,0.00002407398,0.0000988626,0.0003483762,0.0004634186,0.00588319],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005827695,"threshold_uncertainty_score":0.01949561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01856930456376762,"score_gpt":0.2903201763842542,"score_spread":0.2717508718204866,"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."}}