{"id":"W2099114783","doi":"10.1109/tvcg.2012.298","title":"Interactive Rendering of Acquired Materials on Dynamic Geometry Using Frequency Analysis","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Agence Nationale de la Recherche","keywords":"Pixel; Computer science; Shading; Computer vision; Rendering (computer graphics); Global illumination; Precomputation; Artificial intelligence; Specular reflection; Photometric stereo; Image-based lighting; Computer graphics (images); Image-based modeling and rendering; Optics; Image (mathematics); Algorithm; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003629641,0.001204547,0.0006378666,0.001034705,0.000294841,0.001582417,0.0007014137,0.0005421609,0.009390363],"category_scores_gemma":[0.001240104,0.0004908251,0.0008618556,0.000470968,0.0004829892,0.0007851016,0.001565507,0.0008976309,0.0009048143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005791139,"about_ca_system_score_gemma":0.0005069857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001763431,"about_ca_topic_score_gemma":0.003569418,"domain_scores_codex":[0.9998178,0.00003059111,0.000007735794,0.00002143545,0.00009247365,0.00002995111],"domain_scores_gemma":[0.9995298,0.0002442752,0.00003742407,0.00008321323,0.00005993555,0.00004539036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006994969,0.0002579776,0.002345311,0.0005255941,0.0001553802,0.001089638,0.001329127,0.408757,0.3220881,0.0242527,0.01310812,0.2253915],"study_design_scores_gemma":[0.00008130326,0.0001051083,0.002646847,0.00005580729,0.00003965157,0.0005141024,0.0001830206,0.9323547,0.04042717,0.008961549,0.01454975,0.00008099634],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0771819,0.0001840351,0.9044522,0.0003017774,0.00009812548,0.0001035768,0.0005468109,0.008527676,0.008603839],"genre_scores_gemma":[0.4402866,0.0004988019,0.5510344,0.0001501744,0.0000856598,0.0001422455,0.0007186475,0.002881996,0.004201351],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009390363,"threshold_uncertainty_score":0.03141385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02030850509125741,"score_gpt":0.2996543241515157,"score_spread":0.2793458190602582,"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."}}