{"id":"W1867747937","doi":"10.1109/ccece.2000.849637","title":"A VHDL implementation of a shearing unit for shear-warp factorization volume rendering","year":2002,"lang":"en","type":"article","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Rendering (computer graphics); Voxel; Path tracing; Shearing (physics); Volume rendering; Factorization; Computer graphics (images); Algorithm; Computer hardware; Computer vision; Engineering","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":[0.0001403272,0.00007876828,0.0001008426,0.0001857086,0.00007000948,0.00009078305,0.0002621808,0.00003288219,0.00004814147],"category_scores_gemma":[0.00000748477,0.00008121825,0.0000515765,0.0004309894,0.000009554533,0.0003907893,0.0001059744,0.00003032107,0.00000147405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001539124,"about_ca_system_score_gemma":0.00001146614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007687144,"about_ca_topic_score_gemma":0.0000125599,"domain_scores_codex":[0.9992324,0.0000187265,0.0002569621,0.0002034613,0.0001498654,0.0001386024],"domain_scores_gemma":[0.9994729,0.00002875765,0.00009311816,0.0002270238,0.0001419812,0.00003620143],"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":[0.00000125944,0.00007612244,0.01394495,0.0000722211,0.00002340815,3.519434e-7,0.002974817,0.00003277759,0.002155014,0.8921544,0.002117984,0.08644672],"study_design_scores_gemma":[0.0003368759,0.0002070292,0.008105094,0.00001827034,0.000004860577,0.00000186725,0.0001010522,0.9603297,0.02210362,0.005114073,0.003506667,0.0001708706],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005842428,0.00001593197,0.9931717,0.0001372832,0.00009432932,0.0002388993,0.000002311127,0.0002458437,0.0002512961],"genre_scores_gemma":[0.933654,0.00001761971,0.06608116,0.00006020589,0.00002540334,0.00002449815,0.000006750853,0.000007646864,0.0001227354],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9602969,"threshold_uncertainty_score":0.3311984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06607782832901839,"score_gpt":0.3329814248342334,"score_spread":0.266903596505215,"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."}}