{"id":"W3021556530","doi":"10.3390/ijgi9050315","title":"Disdyakis Triacontahedron DGGS","year":2020,"lang":"en","type":"article","venue":"ISPRS International Journal of Geo-Information","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; University of Calgary","keywords":"Computer science; Grid; Rendering (computer graphics); Modular design; Projection (relational algebra); Atlas (anatomy); Visualization; Polyhedron; Computer graphics (images); Algorithm; Theoretical computer science; Data mining; Mathematics; Geometry","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":[0.0002931732,0.0004910275,0.0004818334,0.0005900762,0.0004736764,0.001261787,0.0008993071,0.0003912516,0.01160504],"category_scores_gemma":[0.001241236,0.0002410992,0.0007114348,0.001056344,0.0005149225,0.0009062414,0.001896486,0.0009720701,0.003662412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006397076,"about_ca_system_score_gemma":0.0007434503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003176159,"about_ca_topic_score_gemma":0.004291069,"domain_scores_codex":[0.9995259,0.0000743713,0.000032636,0.00007928782,0.0002358885,0.00005190245],"domain_scores_gemma":[0.999526,0.00007999509,0.00002781821,0.0001724925,0.0001504402,0.00004321598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005082235,0.0001187832,0.003522632,0.0003964312,0.00006182564,0.0006013988,0.0007755454,0.2150823,0.04910867,0.2613117,0.04188393,0.4266286],"study_design_scores_gemma":[0.00008885717,0.0002182671,0.001002937,0.00003971499,0.00001727199,0.0007145552,0.0005370469,0.7459911,0.03529245,0.08044012,0.1356023,0.00005540224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02090331,0.00006170684,0.9575974,0.0002138995,0.0001207196,0.0001103509,0.001004872,0.003053932,0.01693368],"genre_scores_gemma":[0.2330909,0.0001874002,0.7507831,0.0001511235,0.00003282676,0.0003281251,0.003176542,0.0007983713,0.0114516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01160504,"threshold_uncertainty_score":0.03882277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009389327279779803,"score_gpt":0.2336411249663226,"score_spread":0.2242517976865428,"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."}}