{"id":"W3190525204","doi":"10.1111/cgf.14427","title":"Dynamic Diffuse Global Illumination Resampling","year":2021,"lang":"en","type":"preprint","venue":"Computer Graphics Forum","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Global illumination; Specular reflection; Scattering; Resampling; Computer science; Path tracing; Ray tracing (physics); Sampling (signal processing); Variance (accounting); Path (computing); Importance sampling; Sample (material); Computer vision; Artificial intelligence; Algorithm; Optics; Mathematics; Physics; Monte Carlo method; Statistics; Rendering (computer graphics)","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":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.0005169841,0.0007303572,0.000718551,0.000682454,0.0003858641,0.002272787,0.003424616,0.0007100581,0.000004222184],"category_scores_gemma":[0.00002698412,0.0008267691,0.0006721478,0.001729797,0.0001492056,0.0005734903,0.008960644,0.0009587992,0.000005041041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002142326,"about_ca_system_score_gemma":0.0003422197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008046407,"about_ca_topic_score_gemma":0.0001397571,"domain_scores_codex":[0.9953673,0.0002332538,0.0009133258,0.001852862,0.0008611963,0.0007719956],"domain_scores_gemma":[0.9956516,0.0001119306,0.0005667732,0.002578546,0.0008241506,0.0002669768],"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":[0.000002784817,0.0003163403,0.00149034,0.000179887,0.0001294657,0.00006634265,0.0003594237,0.0002127905,0.000005229931,0.9670585,0.001917204,0.02826173],"study_design_scores_gemma":[0.0003151697,0.00008942231,0.003456838,0.0003817542,0.00002391378,0.00004004265,0.00001283765,0.8488914,0.0000565188,0.1436722,0.002258981,0.0008009212],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01251451,0.00107294,0.9786071,0.001031556,0.004341661,0.0005522621,0.0000383281,0.001733817,0.0001078859],"genre_scores_gemma":[0.7206659,0.001087549,0.2749039,0.002372227,0.0002244273,0.0001070553,0.0005439069,0.0000709394,0.0000240633],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8486786,"threshold_uncertainty_score":0.9994183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01954091065229879,"score_gpt":0.299100547632575,"score_spread":0.2795596369802762,"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."}}