{"id":"W2043759714","doi":"10.1007/s00371-006-0055-x","title":"Correlated visibility sampling for direct illumination","year":2006,"lang":"en","type":"article","venue":"The Visual Computer","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Visibility; Sampling (signal processing); Bidirectional reflectance distribution function; Computer science; Global illumination; Variance (accounting); Monte Carlo method; Computer vision; Importance sampling; Noise (video); Computer graphics; Artificial intelligence; Computer graphics (images); Mathematics; Statistics; Image (mathematics); Reflectivity; Optics; Rendering (computer graphics); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007152602,0.0001680117,0.0001742197,0.0001388614,0.0003276832,0.0003264715,0.000737483,0.00007116776,0.000003479307],"category_scores_gemma":[0.00001311084,0.0001252824,0.0001315199,0.000560974,0.00005880284,0.0002646246,0.0003023515,0.00009921822,0.000007598778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003651554,"about_ca_system_score_gemma":0.00002786539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005473982,"about_ca_topic_score_gemma":0.000007804376,"domain_scores_codex":[0.9986489,0.0001048294,0.0003382966,0.0004257227,0.0002239719,0.000258231],"domain_scores_gemma":[0.9987507,0.0003638846,0.0001345672,0.0004675999,0.0002459517,0.00003731185],"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":[0.00002027604,0.0003808335,0.0008985127,0.00003943912,0.00003689692,0.00000205877,0.0005101966,0.0009675698,0.0004431013,0.8526534,0.009393775,0.1346539],"study_design_scores_gemma":[0.0002382811,0.0001970848,0.006750734,0.00001821204,0.000006960201,0.000004954837,0.000001686696,0.9572497,0.002720858,0.02536314,0.007250645,0.0001977495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02851513,0.00004649291,0.9692042,0.0002668699,0.0005553422,0.0004703266,0.000002881769,0.0006931773,0.0002455344],"genre_scores_gemma":[0.9493859,0.000003910563,0.04965198,0.0004185594,0.0003672838,0.00004020816,0.00002565169,0.00001562073,0.00009089376],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9562821,"threshold_uncertainty_score":0.510887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02452251248662878,"score_gpt":0.3186654539345044,"score_spread":0.2941429414478756,"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."}}