{"id":"W2011793254","doi":"10.1145/2766992","title":"Adaptive rendering with linear predictions","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Rendering (computer graphics); Pixel; Computer science; Algorithm; Linear model; Ground truth; Artificial intelligence; Global illumination; Machine learning","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":[0.0004706351,0.0007952485,0.0006869874,0.0004694994,0.0003099145,0.00122838,0.001607617,0.0009116986,0.002862819],"category_scores_gemma":[0.002682411,0.0005785771,0.0008659372,0.000390686,0.0007351139,0.001358558,0.001267829,0.002004922,0.0009624101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005196921,"about_ca_system_score_gemma":0.0009260768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003872349,"about_ca_topic_score_gemma":0.003433467,"domain_scores_codex":[0.9994071,0.0000731508,0.0000207791,0.0001060484,0.0003538221,0.00003921781],"domain_scores_gemma":[0.9991762,0.0003458907,0.00008142207,0.0002069251,0.000148361,0.00004110994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002297867,0.0001216246,0.001277695,0.0001123261,0.00006523042,0.0001923949,0.0002985266,0.6554184,0.06338692,0.03648301,0.00411963,0.2382944],"study_design_scores_gemma":[0.000008354319,0.00001138093,0.00004833106,0.000003128743,0.00000436649,0.0000329988,0.000004355183,0.9911928,0.00498445,0.00231966,0.001381124,0.000009187421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003699528,0.00003870469,0.9943786,0.0000473359,0.00001841289,0.00001330889,0.00001648077,0.000870093,0.0009174951],"genre_scores_gemma":[0.1978309,0.00017591,0.7970843,0.0001375071,0.00005690222,0.00007654884,0.0001341066,0.0007610739,0.00374268],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003872349,"threshold_uncertainty_score":0.009577036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06121532519200461,"score_gpt":0.2908885305530646,"score_spread":0.22967320536106,"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."}}